# data_list remains the same

    Code
      lapply(models, "[[", "data_list")
    Output
      $m0a
      $m0a$M_lvlone
          O1 (Intercept)
      1    2           1
      2    4           1
      3    3           1
      4    2           1
      5    3           1
      6    1           1
      7    3           1
      8    4           1
      9    4           1
      10   2           1
      11   1           1
      12   3           1
      13   3           1
      14   1           1
      15   1           1
      16   4           1
      17   2           1
      18   3           1
      19   4           1
      20   1           1
      21   3           1
      22   4           1
      23   4           1
      24   2           1
      25   1           1
      26   3           1
      27   4           1
      28   1           1
      29   4           1
      30   4           1
      31   2           1
      32   3           1
      33   3           1
      34   1           1
      35   1           1
      36   4           1
      37   4           1
      38   4           1
      39   1           1
      40   2           1
      41   1           1
      42   1           1
      43   2           1
      44   2           1
      45   1           1
      46   1           1
      47   4           1
      48   4           1
      49   2           1
      50   2           1
      51   1           1
      52   3           1
      53   1           1
      54   3           1
      55   2           1
      56   4           1
      57   2           1
      58   1           1
      59   1           1
      60   4           1
      61   2           1
      62   4           1
      63   3           1
      64   2           1
      65   3           1
      66   3           1
      67   2           1
      68   1           1
      69   1           1
      70   1           1
      71   1           1
      72   3           1
      73   2           1
      74   2           1
      75   3           1
      76   3           1
      77   4           1
      78   3           1
      79   2           1
      80   2           1
      81   3           1
      82   1           1
      83   3           1
      84   2           1
      85   2           1
      86   4           1
      87   3           1
      88   2           1
      89   3           1
      90   3           1
      91   4           1
      92   1           1
      93   4           1
      94   1           1
      95   1           1
      96   3           1
      97   1           1
      98   3           1
      99   3           1
      100  3           1
      
      $m0a$mu_delta_ordinal
      [1] 0
      
      $m0a$tau_delta_ordinal
      [1] 1e-04
      
      
      $m0b
      $m0b$M_lvlone
          O2 (Intercept)
      1    4           1
      2    4           1
      3    4           1
      4    1           1
      5    2           1
      6    3           1
      7    4           1
      8    2           1
      9    4           1
      10   3           1
      11   2           1
      12   1           1
      13   1           1
      14   1           1
      15   4           1
      16   3           1
      17   3           1
      18   1           1
      19   3           1
      20   1           1
      21   3           1
      22   3           1
      23   2           1
      24   3           1
      25   2           1
      26   2           1
      27   1           1
      28   4           1
      29   3           1
      30   3           1
      31   2           1
      32   2           1
      33   1           1
      34   1           1
      35   4           1
      36   3           1
      37   3           1
      38   1           1
      39   2           1
      40   3           1
      41   3           1
      42   3           1
      43   3           1
      44   4           1
      45   4           1
      46   1           1
      47   4           1
      48   4           1
      49   1           1
      50   2           1
      51   1           1
      52   3           1
      53   2           1
      54   1           1
      55   2           1
      56   3           1
      57  NA           1
      58   4           1
      59   4           1
      60   3           1
      61   4           1
      62   1           1
      63   4           1
      64   4           1
      65   4           1
      66   1           1
      67   3           1
      68   3           1
      69   4           1
      70   1           1
      71   4           1
      72   4           1
      73   2           1
      74   4           1
      75   3           1
      76   2           1
      77   2           1
      78   3           1
      79   2           1
      80   1           1
      81   4           1
      82   2           1
      83   4           1
      84   1           1
      85   1           1
      86   2           1
      87   3           1
      88   3           1
      89   2           1
      90   4           1
      91   2           1
      92   1           1
      93  NA           1
      94   3           1
      95   1           1
      96   3           1
      97   2           1
      98   2           1
      99   4           1
      100  3           1
      
      $m0b$mu_delta_ordinal
      [1] 0
      
      $m0b$tau_delta_ordinal
      [1] 1e-04
      
      
      $m1a
      $m1a$M_lvlone
          O1 (Intercept)       C1
      1    2           1 1.410531
      2    4           1 1.434183
      3    3           1 1.430994
      4    2           1 1.453096
      5    3           1 1.438344
      6    1           1 1.453207
      7    3           1 1.425176
      8    4           1 1.437908
      9    4           1 1.416911
      10   2           1 1.448638
      11   1           1 1.428375
      12   3           1 1.450130
      13   3           1 1.420545
      14   1           1 1.423005
      15   1           1 1.435902
      16   4           1 1.423901
      17   2           1 1.457208
      18   3           1 1.414280
      19   4           1 1.443383
      20   1           1 1.434954
      21   3           1 1.429499
      22   4           1 1.441897
      23   4           1 1.423713
      24   2           1 1.435395
      25   1           1 1.425944
      26   3           1 1.437115
      27   4           1 1.441326
      28   1           1 1.422953
      29   4           1 1.437797
      30   4           1 1.472121
      31   2           1 1.421782
      32   3           1 1.457672
      33   3           1 1.430842
      34   1           1 1.431523
      35   1           1 1.421395
      36   4           1 1.434496
      37   4           1 1.425383
      38   4           1 1.421802
      39   1           1 1.430094
      40   2           1 1.447621
      41   1           1 1.434797
      42   1           1 1.446091
      43   2           1 1.445306
      44   2           1 1.448783
      45   1           1 1.450617
      46   1           1 1.415055
      47   4           1 1.436590
      48   4           1 1.433938
      49   2           1 1.414941
      50   2           1 1.421807
      51   1           1 1.453203
      52   3           1 1.452129
      53   1           1 1.431510
      54   3           1 1.430082
      55   2           1 1.443492
      56   4           1 1.436460
      57   2           1 1.418119
      58   1           1 1.434971
      59   1           1 1.445599
      60   4           1 1.437097
      61   2           1 1.428360
      62   4           1 1.440550
      63   3           1 1.443014
      64   2           1 1.424298
      65   3           1 1.448823
      66   3           1 1.425834
      67   2           1 1.427102
      68   1           1 1.414240
      69   1           1 1.456218
      70   1           1 1.470594
      71   1           1 1.425058
      72   3           1 1.432371
      73   2           1 1.441656
      74   2           1 1.434952
      75   3           1 1.402860
      76   3           1 1.453363
      77   4           1 1.432909
      78   3           1 1.435103
      79   2           1 1.434462
      80   2           1 1.434661
      81   3           1 1.445881
      82   1           1 1.442548
      83   3           1 1.430097
      84   2           1 1.430119
      85   2           1 1.430315
      86   4           1 1.437584
      87   3           1 1.409738
      88   2           1 1.422388
      89   3           1 1.422509
      90   3           1 1.439432
      91   4           1 1.430175
      92   1           1 1.418002
      93   4           1 1.423812
      94   1           1 1.423473
      95   1           1 1.434412
      96   3           1 1.450844
      97   1           1 1.433371
      98   3           1 1.444378
      99   3           1 1.422523
      100  3           1 1.410394
      
      $m1a$spM_lvlone
                    center      scale
      O1                NA         NA
      (Intercept)       NA         NA
      C1          1.434101 0.01299651
      
      $m1a$mu_reg_ordinal
      [1] 0
      
      $m1a$tau_reg_ordinal
      [1] 1e-04
      
      $m1a$mu_delta_ordinal
      [1] 0
      
      $m1a$tau_delta_ordinal
      [1] 1e-04
      
      
      $m1b
      $m1b$M_lvlone
          O2 (Intercept)       C1
      1    4           1 1.410531
      2    4           1 1.434183
      3    4           1 1.430994
      4    1           1 1.453096
      5    2           1 1.438344
      6    3           1 1.453207
      7    4           1 1.425176
      8    2           1 1.437908
      9    4           1 1.416911
      10   3           1 1.448638
      11   2           1 1.428375
      12   1           1 1.450130
      13   1           1 1.420545
      14   1           1 1.423005
      15   4           1 1.435902
      16   3           1 1.423901
      17   3           1 1.457208
      18   1           1 1.414280
      19   3           1 1.443383
      20   1           1 1.434954
      21   3           1 1.429499
      22   3           1 1.441897
      23   2           1 1.423713
      24   3           1 1.435395
      25   2           1 1.425944
      26   2           1 1.437115
      27   1           1 1.441326
      28   4           1 1.422953
      29   3           1 1.437797
      30   3           1 1.472121
      31   2           1 1.421782
      32   2           1 1.457672
      33   1           1 1.430842
      34   1           1 1.431523
      35   4           1 1.421395
      36   3           1 1.434496
      37   3           1 1.425383
      38   1           1 1.421802
      39   2           1 1.430094
      40   3           1 1.447621
      41   3           1 1.434797
      42   3           1 1.446091
      43   3           1 1.445306
      44   4           1 1.448783
      45   4           1 1.450617
      46   1           1 1.415055
      47   4           1 1.436590
      48   4           1 1.433938
      49   1           1 1.414941
      50   2           1 1.421807
      51   1           1 1.453203
      52   3           1 1.452129
      53   2           1 1.431510
      54   1           1 1.430082
      55   2           1 1.443492
      56   3           1 1.436460
      57  NA           1 1.418119
      58   4           1 1.434971
      59   4           1 1.445599
      60   3           1 1.437097
      61   4           1 1.428360
      62   1           1 1.440550
      63   4           1 1.443014
      64   4           1 1.424298
      65   4           1 1.448823
      66   1           1 1.425834
      67   3           1 1.427102
      68   3           1 1.414240
      69   4           1 1.456218
      70   1           1 1.470594
      71   4           1 1.425058
      72   4           1 1.432371
      73   2           1 1.441656
      74   4           1 1.434952
      75   3           1 1.402860
      76   2           1 1.453363
      77   2           1 1.432909
      78   3           1 1.435103
      79   2           1 1.434462
      80   1           1 1.434661
      81   4           1 1.445881
      82   2           1 1.442548
      83   4           1 1.430097
      84   1           1 1.430119
      85   1           1 1.430315
      86   2           1 1.437584
      87   3           1 1.409738
      88   3           1 1.422388
      89   2           1 1.422509
      90   4           1 1.439432
      91   2           1 1.430175
      92   1           1 1.418002
      93  NA           1 1.423812
      94   3           1 1.423473
      95   1           1 1.434412
      96   3           1 1.450844
      97   2           1 1.433371
      98   2           1 1.444378
      99   4           1 1.422523
      100  3           1 1.410394
      
      $m1b$spM_lvlone
                    center      scale
      O2                NA         NA
      (Intercept)       NA         NA
      C1          1.434101 0.01299651
      
      $m1b$mu_reg_ordinal
      [1] 0
      
      $m1b$tau_reg_ordinal
      [1] 1e-04
      
      $m1b$mu_delta_ordinal
      [1] 0
      
      $m1b$tau_delta_ordinal
      [1] 1e-04
      
      
      $m2a
      $m2a$M_lvlone
          O1           C2 (Intercept)
      1    2  0.144065882           1
      2    4  0.032778478           1
      3    3  0.343008492           1
      4    2 -0.361887858           1
      5    3 -0.389600647           1
      6    1 -0.205306841           1
      7    3  0.079434830           1
      8    4 -0.331246757           1
      9    4 -0.329638800           1
      10   2  0.167597533           1
      11   1  0.860207989           1
      12   3  0.022730640           1
      13   3  0.217171172           1
      14   1 -0.403002412           1
      15   1  0.087369742           1
      16   4 -0.183870429           1
      17   2 -0.194577002           1
      18   3 -0.349718516           1
      19   4 -0.508781244           1
      20   1  0.494883111           1
      21   3  0.258041067           1
      22   4 -0.922621989           1
      23   4  0.431254949           1
      24   2 -0.294218881           1
      25   1 -0.425548895           1
      26   3  0.057176054           1
      27   4  0.289090158           1
      28   1 -0.473079489           1
      29   4 -0.385664863           1
      30   4 -0.154780107           1
      31   2  0.100536296           1
      32   3  0.634791958           1
      33   3 -0.387252617           1
      34   1 -0.181741088           1
      35   1 -0.311562695           1
      36   4 -0.044115907           1
      37   4 -0.657409991           1
      38   4  0.159577214           1
      39   1 -0.460416933           1
      40   2           NA           1
      41   1 -0.248909867           1
      42   1 -0.609021545           1
      43   2  0.025471883           1
      44   2  0.066648592           1
      45   1 -0.276108719           1
      46   1 -0.179737577           1
      47   4  0.181190937           1
      48   4 -0.453871693           1
      49   2  0.448629602           1
      50   2 -0.529811821           1
      51   1 -0.028304571           1
      52   3 -0.520318482           1
      53   1  0.171317619           1
      54   3  0.432732046           1
      55   2 -0.346286005           1
      56   4 -0.469375653           1
      57   2  0.031021711           1
      58   1 -0.118837515           1
      59   1  0.507769984           1
      60   4  0.271797031           1
      61   2 -0.124442204           1
      62   4  0.277677389           1
      63   3 -0.102893730           1
      64   2           NA           1
      65   3 -0.678303052           1
      66   3  0.478880037           1
      67   2 -0.428028760           1
      68   1  0.048119185           1
      69   1  0.216932805           1
      70   1 -0.234575269           1
      71   1  0.006827078           1
      72   3 -0.456055171           1
      73   2  0.346486708           1
      74   2  0.205092215           1
      75   3 -0.136596858           1
      76   3 -0.500179043           1
      77   4  0.527352086           1
      78   3  0.022742250           1
      79   2           NA           1
      80   2 -0.002032440           1
      81   3 -0.154246160           1
      82   1  0.140201825           1
      83   3 -0.141417121           1
      84   2           NA           1
      85   2 -0.021285339           1
      86   4 -0.010196306           1
      87   3 -0.089747520           1
      88   2 -0.083699898           1
      89   3 -0.044061996           1
      90   3 -0.209291697           1
      91   4  0.639036426           1
      92   1  0.094698299           1
      93   4 -0.055510622           1
      94   1 -0.421318463           1
      95   1  0.125295503           1
      96   3  0.213084904           1
      97   1 -0.161914659           1
      98   3 -0.034767685           1
      99   3 -0.320681689           1
      100  3  0.058192962           1
      
      $m2a$spM_lvlone
                       center     scale
      O1                   NA        NA
      C2          -0.06490582 0.3331735
      (Intercept)          NA        NA
      
      $m2a$mu_reg_norm
      [1] 0
      
      $m2a$tau_reg_norm
      [1] 1e-04
      
      $m2a$shape_tau_norm
      [1] 0.01
      
      $m2a$rate_tau_norm
      [1] 0.01
      
      $m2a$mu_reg_ordinal
      [1] 0
      
      $m2a$tau_reg_ordinal
      [1] 1e-04
      
      $m2a$mu_delta_ordinal
      [1] 0
      
      $m2a$tau_delta_ordinal
      [1] 1e-04
      
      
      $m2b
      $m2b$M_lvlone
          O2           C2 (Intercept)
      1    4  0.144065882           1
      2    4  0.032778478           1
      3    4  0.343008492           1
      4    1 -0.361887858           1
      5    2 -0.389600647           1
      6    3 -0.205306841           1
      7    4  0.079434830           1
      8    2 -0.331246757           1
      9    4 -0.329638800           1
      10   3  0.167597533           1
      11   2  0.860207989           1
      12   1  0.022730640           1
      13   1  0.217171172           1
      14   1 -0.403002412           1
      15   4  0.087369742           1
      16   3 -0.183870429           1
      17   3 -0.194577002           1
      18   1 -0.349718516           1
      19   3 -0.508781244           1
      20   1  0.494883111           1
      21   3  0.258041067           1
      22   3 -0.922621989           1
      23   2  0.431254949           1
      24   3 -0.294218881           1
      25   2 -0.425548895           1
      26   2  0.057176054           1
      27   1  0.289090158           1
      28   4 -0.473079489           1
      29   3 -0.385664863           1
      30   3 -0.154780107           1
      31   2  0.100536296           1
      32   2  0.634791958           1
      33   1 -0.387252617           1
      34   1 -0.181741088           1
      35   4 -0.311562695           1
      36   3 -0.044115907           1
      37   3 -0.657409991           1
      38   1  0.159577214           1
      39   2 -0.460416933           1
      40   3           NA           1
      41   3 -0.248909867           1
      42   3 -0.609021545           1
      43   3  0.025471883           1
      44   4  0.066648592           1
      45   4 -0.276108719           1
      46   1 -0.179737577           1
      47   4  0.181190937           1
      48   4 -0.453871693           1
      49   1  0.448629602           1
      50   2 -0.529811821           1
      51   1 -0.028304571           1
      52   3 -0.520318482           1
      53   2  0.171317619           1
      54   1  0.432732046           1
      55   2 -0.346286005           1
      56   3 -0.469375653           1
      57  NA  0.031021711           1
      58   4 -0.118837515           1
      59   4  0.507769984           1
      60   3  0.271797031           1
      61   4 -0.124442204           1
      62   1  0.277677389           1
      63   4 -0.102893730           1
      64   4           NA           1
      65   4 -0.678303052           1
      66   1  0.478880037           1
      67   3 -0.428028760           1
      68   3  0.048119185           1
      69   4  0.216932805           1
      70   1 -0.234575269           1
      71   4  0.006827078           1
      72   4 -0.456055171           1
      73   2  0.346486708           1
      74   4  0.205092215           1
      75   3 -0.136596858           1
      76   2 -0.500179043           1
      77   2  0.527352086           1
      78   3  0.022742250           1
      79   2           NA           1
      80   1 -0.002032440           1
      81   4 -0.154246160           1
      82   2  0.140201825           1
      83   4 -0.141417121           1
      84   1           NA           1
      85   1 -0.021285339           1
      86   2 -0.010196306           1
      87   3 -0.089747520           1
      88   3 -0.083699898           1
      89   2 -0.044061996           1
      90   4 -0.209291697           1
      91   2  0.639036426           1
      92   1  0.094698299           1
      93  NA -0.055510622           1
      94   3 -0.421318463           1
      95   1  0.125295503           1
      96   3  0.213084904           1
      97   2 -0.161914659           1
      98   2 -0.034767685           1
      99   4 -0.320681689           1
      100  3  0.058192962           1
      
      $m2b$spM_lvlone
                       center     scale
      O2                   NA        NA
      C2          -0.06490582 0.3331735
      (Intercept)          NA        NA
      
      $m2b$mu_reg_norm
      [1] 0
      
      $m2b$tau_reg_norm
      [1] 1e-04
      
      $m2b$shape_tau_norm
      [1] 0.01
      
      $m2b$rate_tau_norm
      [1] 0.01
      
      $m2b$mu_reg_ordinal
      [1] 0
      
      $m2b$tau_reg_ordinal
      [1] 1e-04
      
      $m2b$mu_delta_ordinal
      [1] 0
      
      $m2b$tau_delta_ordinal
      [1] 1e-04
      
      
      $m3a
      $m3a$M_lvlone
                C1 (Intercept)       O1.L O1.Q       O1.C
      1   1.410531           1 -0.2236068 -0.5  0.6708204
      2   1.434183           1  0.6708204  0.5  0.2236068
      3   1.430994           1  0.2236068 -0.5 -0.6708204
      4   1.453096           1 -0.2236068 -0.5  0.6708204
      5   1.438344           1  0.2236068 -0.5 -0.6708204
      6   1.453207           1 -0.6708204  0.5 -0.2236068
      7   1.425176           1  0.2236068 -0.5 -0.6708204
      8   1.437908           1  0.6708204  0.5  0.2236068
      9   1.416911           1  0.6708204  0.5  0.2236068
      10  1.448638           1 -0.2236068 -0.5  0.6708204
      11  1.428375           1 -0.6708204  0.5 -0.2236068
      12  1.450130           1  0.2236068 -0.5 -0.6708204
      13  1.420545           1  0.2236068 -0.5 -0.6708204
      14  1.423005           1 -0.6708204  0.5 -0.2236068
      15  1.435902           1 -0.6708204  0.5 -0.2236068
      16  1.423901           1  0.6708204  0.5  0.2236068
      17  1.457208           1 -0.2236068 -0.5  0.6708204
      18  1.414280           1  0.2236068 -0.5 -0.6708204
      19  1.443383           1  0.6708204  0.5  0.2236068
      20  1.434954           1 -0.6708204  0.5 -0.2236068
      21  1.429499           1  0.2236068 -0.5 -0.6708204
      22  1.441897           1  0.6708204  0.5  0.2236068
      23  1.423713           1  0.6708204  0.5  0.2236068
      24  1.435395           1 -0.2236068 -0.5  0.6708204
      25  1.425944           1 -0.6708204  0.5 -0.2236068
      26  1.437115           1  0.2236068 -0.5 -0.6708204
      27  1.441326           1  0.6708204  0.5  0.2236068
      28  1.422953           1 -0.6708204  0.5 -0.2236068
      29  1.437797           1  0.6708204  0.5  0.2236068
      30  1.472121           1  0.6708204  0.5  0.2236068
      31  1.421782           1 -0.2236068 -0.5  0.6708204
      32  1.457672           1  0.2236068 -0.5 -0.6708204
      33  1.430842           1  0.2236068 -0.5 -0.6708204
      34  1.431523           1 -0.6708204  0.5 -0.2236068
      35  1.421395           1 -0.6708204  0.5 -0.2236068
      36  1.434496           1  0.6708204  0.5  0.2236068
      37  1.425383           1  0.6708204  0.5  0.2236068
      38  1.421802           1  0.6708204  0.5  0.2236068
      39  1.430094           1 -0.6708204  0.5 -0.2236068
      40  1.447621           1 -0.2236068 -0.5  0.6708204
      41  1.434797           1 -0.6708204  0.5 -0.2236068
      42  1.446091           1 -0.6708204  0.5 -0.2236068
      43  1.445306           1 -0.2236068 -0.5  0.6708204
      44  1.448783           1 -0.2236068 -0.5  0.6708204
      45  1.450617           1 -0.6708204  0.5 -0.2236068
      46  1.415055           1 -0.6708204  0.5 -0.2236068
      47  1.436590           1  0.6708204  0.5  0.2236068
      48  1.433938           1  0.6708204  0.5  0.2236068
      49  1.414941           1 -0.2236068 -0.5  0.6708204
      50  1.421807           1 -0.2236068 -0.5  0.6708204
      51  1.453203           1 -0.6708204  0.5 -0.2236068
      52  1.452129           1  0.2236068 -0.5 -0.6708204
      53  1.431510           1 -0.6708204  0.5 -0.2236068
      54  1.430082           1  0.2236068 -0.5 -0.6708204
      55  1.443492           1 -0.2236068 -0.5  0.6708204
      56  1.436460           1  0.6708204  0.5  0.2236068
      57  1.418119           1 -0.2236068 -0.5  0.6708204
      58  1.434971           1 -0.6708204  0.5 -0.2236068
      59  1.445599           1 -0.6708204  0.5 -0.2236068
      60  1.437097           1  0.6708204  0.5  0.2236068
      61  1.428360           1 -0.2236068 -0.5  0.6708204
      62  1.440550           1  0.6708204  0.5  0.2236068
      63  1.443014           1  0.2236068 -0.5 -0.6708204
      64  1.424298           1 -0.2236068 -0.5  0.6708204
      65  1.448823           1  0.2236068 -0.5 -0.6708204
      66  1.425834           1  0.2236068 -0.5 -0.6708204
      67  1.427102           1 -0.2236068 -0.5  0.6708204
      68  1.414240           1 -0.6708204  0.5 -0.2236068
      69  1.456218           1 -0.6708204  0.5 -0.2236068
      70  1.470594           1 -0.6708204  0.5 -0.2236068
      71  1.425058           1 -0.6708204  0.5 -0.2236068
      72  1.432371           1  0.2236068 -0.5 -0.6708204
      73  1.441656           1 -0.2236068 -0.5  0.6708204
      74  1.434952           1 -0.2236068 -0.5  0.6708204
      75  1.402860           1  0.2236068 -0.5 -0.6708204
      76  1.453363           1  0.2236068 -0.5 -0.6708204
      77  1.432909           1  0.6708204  0.5  0.2236068
      78  1.435103           1  0.2236068 -0.5 -0.6708204
      79  1.434462           1 -0.2236068 -0.5  0.6708204
      80  1.434661           1 -0.2236068 -0.5  0.6708204
      81  1.445881           1  0.2236068 -0.5 -0.6708204
      82  1.442548           1 -0.6708204  0.5 -0.2236068
      83  1.430097           1  0.2236068 -0.5 -0.6708204
      84  1.430119           1 -0.2236068 -0.5  0.6708204
      85  1.430315           1 -0.2236068 -0.5  0.6708204
      86  1.437584           1  0.6708204  0.5  0.2236068
      87  1.409738           1  0.2236068 -0.5 -0.6708204
      88  1.422388           1 -0.2236068 -0.5  0.6708204
      89  1.422509           1  0.2236068 -0.5 -0.6708204
      90  1.439432           1  0.2236068 -0.5 -0.6708204
      91  1.430175           1  0.6708204  0.5  0.2236068
      92  1.418002           1 -0.6708204  0.5 -0.2236068
      93  1.423812           1  0.6708204  0.5  0.2236068
      94  1.423473           1 -0.6708204  0.5 -0.2236068
      95  1.434412           1 -0.6708204  0.5 -0.2236068
      96  1.450844           1  0.2236068 -0.5 -0.6708204
      97  1.433371           1 -0.6708204  0.5 -0.2236068
      98  1.444378           1  0.2236068 -0.5 -0.6708204
      99  1.422523           1  0.2236068 -0.5 -0.6708204
      100 1.410394           1  0.2236068 -0.5 -0.6708204
      
      $m3a$mu_reg_norm
      [1] 0
      
      $m3a$tau_reg_norm
      [1] 1e-04
      
      $m3a$shape_tau_norm
      [1] 0.01
      
      $m3a$rate_tau_norm
      [1] 0.01
      
      
      $m3b
      $m3b$M_lvlone
                C1 O2 (Intercept) O22 O23 O24
      1   1.410531  4           1  NA  NA  NA
      2   1.434183  4           1  NA  NA  NA
      3   1.430994  4           1  NA  NA  NA
      4   1.453096  1           1  NA  NA  NA
      5   1.438344  2           1  NA  NA  NA
      6   1.453207  3           1  NA  NA  NA
      7   1.425176  4           1  NA  NA  NA
      8   1.437908  2           1  NA  NA  NA
      9   1.416911  4           1  NA  NA  NA
      10  1.448638  3           1  NA  NA  NA
      11  1.428375  2           1  NA  NA  NA
      12  1.450130  1           1  NA  NA  NA
      13  1.420545  1           1  NA  NA  NA
      14  1.423005  1           1  NA  NA  NA
      15  1.435902  4           1  NA  NA  NA
      16  1.423901  3           1  NA  NA  NA
      17  1.457208  3           1  NA  NA  NA
      18  1.414280  1           1  NA  NA  NA
      19  1.443383  3           1  NA  NA  NA
      20  1.434954  1           1  NA  NA  NA
      21  1.429499  3           1  NA  NA  NA
      22  1.441897  3           1  NA  NA  NA
      23  1.423713  2           1  NA  NA  NA
      24  1.435395  3           1  NA  NA  NA
      25  1.425944  2           1  NA  NA  NA
      26  1.437115  2           1  NA  NA  NA
      27  1.441326  1           1  NA  NA  NA
      28  1.422953  4           1  NA  NA  NA
      29  1.437797  3           1  NA  NA  NA
      30  1.472121  3           1  NA  NA  NA
      31  1.421782  2           1  NA  NA  NA
      32  1.457672  2           1  NA  NA  NA
      33  1.430842  1           1  NA  NA  NA
      34  1.431523  1           1  NA  NA  NA
      35  1.421395  4           1  NA  NA  NA
      36  1.434496  3           1  NA  NA  NA
      37  1.425383  3           1  NA  NA  NA
      38  1.421802  1           1  NA  NA  NA
      39  1.430094  2           1  NA  NA  NA
      40  1.447621  3           1  NA  NA  NA
      41  1.434797  3           1  NA  NA  NA
      42  1.446091  3           1  NA  NA  NA
      43  1.445306  3           1  NA  NA  NA
      44  1.448783  4           1  NA  NA  NA
      45  1.450617  4           1  NA  NA  NA
      46  1.415055  1           1  NA  NA  NA
      47  1.436590  4           1  NA  NA  NA
      48  1.433938  4           1  NA  NA  NA
      49  1.414941  1           1  NA  NA  NA
      50  1.421807  2           1  NA  NA  NA
      51  1.453203  1           1  NA  NA  NA
      52  1.452129  3           1  NA  NA  NA
      53  1.431510  2           1  NA  NA  NA
      54  1.430082  1           1  NA  NA  NA
      55  1.443492  2           1  NA  NA  NA
      56  1.436460  3           1  NA  NA  NA
      57  1.418119 NA           1  NA  NA  NA
      58  1.434971  4           1  NA  NA  NA
      59  1.445599  4           1  NA  NA  NA
      60  1.437097  3           1  NA  NA  NA
      61  1.428360  4           1  NA  NA  NA
      62  1.440550  1           1  NA  NA  NA
      63  1.443014  4           1  NA  NA  NA
      64  1.424298  4           1  NA  NA  NA
      65  1.448823  4           1  NA  NA  NA
      66  1.425834  1           1  NA  NA  NA
      67  1.427102  3           1  NA  NA  NA
      68  1.414240  3           1  NA  NA  NA
      69  1.456218  4           1  NA  NA  NA
      70  1.470594  1           1  NA  NA  NA
      71  1.425058  4           1  NA  NA  NA
      72  1.432371  4           1  NA  NA  NA
      73  1.441656  2           1  NA  NA  NA
      74  1.434952  4           1  NA  NA  NA
      75  1.402860  3           1  NA  NA  NA
      76  1.453363  2           1  NA  NA  NA
      77  1.432909  2           1  NA  NA  NA
      78  1.435103  3           1  NA  NA  NA
      79  1.434462  2           1  NA  NA  NA
      80  1.434661  1           1  NA  NA  NA
      81  1.445881  4           1  NA  NA  NA
      82  1.442548  2           1  NA  NA  NA
      83  1.430097  4           1  NA  NA  NA
      84  1.430119  1           1  NA  NA  NA
      85  1.430315  1           1  NA  NA  NA
      86  1.437584  2           1  NA  NA  NA
      87  1.409738  3           1  NA  NA  NA
      88  1.422388  3           1  NA  NA  NA
      89  1.422509  2           1  NA  NA  NA
      90  1.439432  4           1  NA  NA  NA
      91  1.430175  2           1  NA  NA  NA
      92  1.418002  1           1  NA  NA  NA
      93  1.423812 NA           1  NA  NA  NA
      94  1.423473  3           1  NA  NA  NA
      95  1.434412  1           1  NA  NA  NA
      96  1.450844  3           1  NA  NA  NA
      97  1.433371  2           1  NA  NA  NA
      98  1.444378  2           1  NA  NA  NA
      99  1.422523  4           1  NA  NA  NA
      100 1.410394  3           1  NA  NA  NA
      
      $m3b$mu_reg_norm
      [1] 0
      
      $m3b$tau_reg_norm
      [1] 1e-04
      
      $m3b$shape_tau_norm
      [1] 0.01
      
      $m3b$rate_tau_norm
      [1] 0.01
      
      $m3b$mu_delta_ordinal
      [1] 0
      
      $m3b$tau_delta_ordinal
      [1] 1e-04
      
      
      $m4a
      $m4a$M_lvlone
          O1           C2 M2 O2 (Intercept) M22 M23 M24 O22 O23 O24 abs(C1 - C2)
      1    2  0.144065882  4  4           1  NA  NA  NA  NA  NA  NA           NA
      2    4  0.032778478  1  4           1  NA  NA  NA  NA  NA  NA           NA
      3    3  0.343008492  3  4           1  NA  NA  NA  NA  NA  NA           NA
      4    2 -0.361887858  3  1           1  NA  NA  NA  NA  NA  NA           NA
      5    3 -0.389600647  4  2           1  NA  NA  NA  NA  NA  NA           NA
      6    1 -0.205306841  4  3           1  NA  NA  NA  NA  NA  NA           NA
      7    3  0.079434830  1  4           1  NA  NA  NA  NA  NA  NA           NA
      8    4 -0.331246757  1  2           1  NA  NA  NA  NA  NA  NA           NA
      9    4 -0.329638800  2  4           1  NA  NA  NA  NA  NA  NA           NA
      10   2  0.167597533  2  3           1  NA  NA  NA  NA  NA  NA           NA
      11   1  0.860207989  3  2           1  NA  NA  NA  NA  NA  NA           NA
      12   3  0.022730640  3  1           1  NA  NA  NA  NA  NA  NA           NA
      13   3  0.217171172  2  1           1  NA  NA  NA  NA  NA  NA           NA
      14   1 -0.403002412  3  1           1  NA  NA  NA  NA  NA  NA           NA
      15   1  0.087369742  2  4           1  NA  NA  NA  NA  NA  NA           NA
      16   4 -0.183870429  1  3           1  NA  NA  NA  NA  NA  NA           NA
      17   2 -0.194577002  4  3           1  NA  NA  NA  NA  NA  NA           NA
      18   3 -0.349718516  2  1           1  NA  NA  NA  NA  NA  NA           NA
      19   4 -0.508781244  3  3           1  NA  NA  NA  NA  NA  NA           NA
      20   1  0.494883111  3  1           1  NA  NA  NA  NA  NA  NA           NA
      21   3  0.258041067  2  3           1  NA  NA  NA  NA  NA  NA           NA
      22   4 -0.922621989  2  3           1  NA  NA  NA  NA  NA  NA           NA
      23   4  0.431254949  3  2           1  NA  NA  NA  NA  NA  NA           NA
      24   2 -0.294218881  3  3           1  NA  NA  NA  NA  NA  NA           NA
      25   1 -0.425548895  2  2           1  NA  NA  NA  NA  NA  NA           NA
      26   3  0.057176054  2  2           1  NA  NA  NA  NA  NA  NA           NA
      27   4  0.289090158  1  1           1  NA  NA  NA  NA  NA  NA           NA
      28   1 -0.473079489  3  4           1  NA  NA  NA  NA  NA  NA           NA
      29   4 -0.385664863  4  3           1  NA  NA  NA  NA  NA  NA           NA
      30   4 -0.154780107  2  3           1  NA  NA  NA  NA  NA  NA           NA
      31   2  0.100536296 NA  2           1  NA  NA  NA  NA  NA  NA           NA
      32   3  0.634791958  4  2           1  NA  NA  NA  NA  NA  NA           NA
      33   3 -0.387252617  4  1           1  NA  NA  NA  NA  NA  NA           NA
      34   1 -0.181741088  4  1           1  NA  NA  NA  NA  NA  NA           NA
      35   1 -0.311562695  2  4           1  NA  NA  NA  NA  NA  NA           NA
      36   4 -0.044115907  1  3           1  NA  NA  NA  NA  NA  NA           NA
      37   4 -0.657409991  3  3           1  NA  NA  NA  NA  NA  NA           NA
      38   4  0.159577214  4  1           1  NA  NA  NA  NA  NA  NA           NA
      39   1 -0.460416933  3  2           1  NA  NA  NA  NA  NA  NA           NA
      40   2           NA  3  3           1  NA  NA  NA  NA  NA  NA           NA
      41   1 -0.248909867  1  3           1  NA  NA  NA  NA  NA  NA           NA
      42   1 -0.609021545  4  3           1  NA  NA  NA  NA  NA  NA           NA
      43   2  0.025471883  1  3           1  NA  NA  NA  NA  NA  NA           NA
      44   2  0.066648592  2  4           1  NA  NA  NA  NA  NA  NA           NA
      45   1 -0.276108719  2  4           1  NA  NA  NA  NA  NA  NA           NA
      46   1 -0.179737577  1  1           1  NA  NA  NA  NA  NA  NA           NA
      47   4  0.181190937  4  4           1  NA  NA  NA  NA  NA  NA           NA
      48   4 -0.453871693  2  4           1  NA  NA  NA  NA  NA  NA           NA
      49   2  0.448629602  4  1           1  NA  NA  NA  NA  NA  NA           NA
      50   2 -0.529811821  1  2           1  NA  NA  NA  NA  NA  NA           NA
      51   1 -0.028304571  4  1           1  NA  NA  NA  NA  NA  NA           NA
      52   3 -0.520318482  4  3           1  NA  NA  NA  NA  NA  NA           NA
      53   1  0.171317619  4  2           1  NA  NA  NA  NA  NA  NA           NA
      54   3  0.432732046  3  1           1  NA  NA  NA  NA  NA  NA           NA
      55   2 -0.346286005  3  2           1  NA  NA  NA  NA  NA  NA           NA
      56   4 -0.469375653  3  3           1  NA  NA  NA  NA  NA  NA           NA
      57   2  0.031021711  2 NA           1  NA  NA  NA  NA  NA  NA           NA
      58   1 -0.118837515  3  4           1  NA  NA  NA  NA  NA  NA           NA
      59   1  0.507769984  3  4           1  NA  NA  NA  NA  NA  NA           NA
      60   4  0.271797031  4  3           1  NA  NA  NA  NA  NA  NA           NA
      61   2 -0.124442204  2  4           1  NA  NA  NA  NA  NA  NA           NA
      62   4  0.277677389  2  1           1  NA  NA  NA  NA  NA  NA           NA
      63   3 -0.102893730  1  4           1  NA  NA  NA  NA  NA  NA           NA
      64   2           NA  2  4           1  NA  NA  NA  NA  NA  NA           NA
      65   3 -0.678303052  2  4           1  NA  NA  NA  NA  NA  NA           NA
      66   3  0.478880037  3  1           1  NA  NA  NA  NA  NA  NA           NA
      67   2 -0.428028760  2  3           1  NA  NA  NA  NA  NA  NA           NA
      68   1  0.048119185  4  3           1  NA  NA  NA  NA  NA  NA           NA
      69   1  0.216932805 NA  4           1  NA  NA  NA  NA  NA  NA           NA
      70   1 -0.234575269  1  1           1  NA  NA  NA  NA  NA  NA           NA
      71   1  0.006827078  2  4           1  NA  NA  NA  NA  NA  NA           NA
      72   3 -0.456055171  3  4           1  NA  NA  NA  NA  NA  NA           NA
      73   2  0.346486708  4  2           1  NA  NA  NA  NA  NA  NA           NA
      74   2  0.205092215  4  4           1  NA  NA  NA  NA  NA  NA           NA
      75   3 -0.136596858  1  3           1  NA  NA  NA  NA  NA  NA           NA
      76   3 -0.500179043  4  2           1  NA  NA  NA  NA  NA  NA           NA
      77   4  0.527352086 NA  2           1  NA  NA  NA  NA  NA  NA           NA
      78   3  0.022742250  2  3           1  NA  NA  NA  NA  NA  NA           NA
      79   2           NA  2  2           1  NA  NA  NA  NA  NA  NA           NA
      80   2 -0.002032440  2  1           1  NA  NA  NA  NA  NA  NA           NA
      81   3 -0.154246160  4  4           1  NA  NA  NA  NA  NA  NA           NA
      82   1  0.140201825  3  2           1  NA  NA  NA  NA  NA  NA           NA
      83   3 -0.141417121  3  4           1  NA  NA  NA  NA  NA  NA           NA
      84   2           NA  1  1           1  NA  NA  NA  NA  NA  NA           NA
      85   2 -0.021285339  2  1           1  NA  NA  NA  NA  NA  NA           NA
      86   4 -0.010196306  1  2           1  NA  NA  NA  NA  NA  NA           NA
      87   3 -0.089747520  3  3           1  NA  NA  NA  NA  NA  NA           NA
      88   2 -0.083699898  1  3           1  NA  NA  NA  NA  NA  NA           NA
      89   3 -0.044061996  2  2           1  NA  NA  NA  NA  NA  NA           NA
      90   3 -0.209291697  1  4           1  NA  NA  NA  NA  NA  NA           NA
      91   4  0.639036426  3  2           1  NA  NA  NA  NA  NA  NA           NA
      92   1  0.094698299  1  1           1  NA  NA  NA  NA  NA  NA           NA
      93   4 -0.055510622  4 NA           1  NA  NA  NA  NA  NA  NA           NA
      94   1 -0.421318463  4  3           1  NA  NA  NA  NA  NA  NA           NA
      95   1  0.125295503  1  1           1  NA  NA  NA  NA  NA  NA           NA
      96   3  0.213084904  4  3           1  NA  NA  NA  NA  NA  NA           NA
      97   1 -0.161914659  4  2           1  NA  NA  NA  NA  NA  NA           NA
      98   3 -0.034767685  3  2           1  NA  NA  NA  NA  NA  NA           NA
      99   3 -0.320681689  3  4           1  NA  NA  NA  NA  NA  NA           NA
      100  3  0.058192962  4  3           1  NA  NA  NA  NA  NA  NA           NA
            log(C1) O22:abs(C1 - C2) O23:abs(C1 - C2) O24:abs(C1 - C2)       C1
      1   0.3439662               NA               NA               NA 1.410531
      2   0.3605954               NA               NA               NA 1.434183
      3   0.3583696               NA               NA               NA 1.430994
      4   0.3736964               NA               NA               NA 1.453096
      5   0.3634928               NA               NA               NA 1.438344
      6   0.3737730               NA               NA               NA 1.453207
      7   0.3542952               NA               NA               NA 1.425176
      8   0.3631892               NA               NA               NA 1.437908
      9   0.3484794               NA               NA               NA 1.416911
      10  0.3706241               NA               NA               NA 1.448638
      11  0.3565373               NA               NA               NA 1.428375
      12  0.3716534               NA               NA               NA 1.450130
      13  0.3510408               NA               NA               NA 1.420545
      14  0.3527707               NA               NA               NA 1.423005
      15  0.3617934               NA               NA               NA 1.435902
      16  0.3534000               NA               NA               NA 1.423901
      17  0.3765220               NA               NA               NA 1.457208
      18  0.3466206               NA               NA               NA 1.414280
      19  0.3669896               NA               NA               NA 1.443383
      20  0.3611331               NA               NA               NA 1.434954
      21  0.3573242               NA               NA               NA 1.429499
      22  0.3659595               NA               NA               NA 1.441897
      23  0.3532680               NA               NA               NA 1.423713
      24  0.3614400               NA               NA               NA 1.435395
      25  0.3548341               NA               NA               NA 1.425944
      26  0.3626380               NA               NA               NA 1.437115
      27  0.3655634               NA               NA               NA 1.441326
      28  0.3527344               NA               NA               NA 1.422953
      29  0.3631120               NA               NA               NA 1.437797
      30  0.3867045               NA               NA               NA 1.472121
      31  0.3519109               NA               NA               NA 1.421782
      32  0.3768405               NA               NA               NA 1.457672
      33  0.3582630               NA               NA               NA 1.430842
      34  0.3587390               NA               NA               NA 1.431523
      35  0.3516387               NA               NA               NA 1.421395
      36  0.3608133               NA               NA               NA 1.434496
      37  0.3544406               NA               NA               NA 1.425383
      38  0.3519254               NA               NA               NA 1.421802
      39  0.3577404               NA               NA               NA 1.430094
      40  0.3699214               NA               NA               NA 1.447621
      41  0.3610235               NA               NA               NA 1.434797
      42  0.3688639               NA               NA               NA 1.446091
      43  0.3683210               NA               NA               NA 1.445306
      44  0.3707242               NA               NA               NA 1.448783
      45  0.3719890               NA               NA               NA 1.450617
      46  0.3471687               NA               NA               NA 1.415055
      47  0.3622725               NA               NA               NA 1.436590
      48  0.3604242               NA               NA               NA 1.433938
      49  0.3470878               NA               NA               NA 1.414941
      50  0.3519288               NA               NA               NA 1.421807
      51  0.3737703               NA               NA               NA 1.453203
      52  0.3730309               NA               NA               NA 1.452129
      53  0.3587298               NA               NA               NA 1.431510
      54  0.3577317               NA               NA               NA 1.430082
      55  0.3670651               NA               NA               NA 1.443492
      56  0.3621821               NA               NA               NA 1.436460
      57  0.3493310               NA               NA               NA 1.418119
      58  0.3611449               NA               NA               NA 1.434971
      59  0.3685236               NA               NA               NA 1.445599
      60  0.3626252               NA               NA               NA 1.437097
      61  0.3565271               NA               NA               NA 1.428360
      62  0.3650248               NA               NA               NA 1.440550
      63  0.3667342               NA               NA               NA 1.443014
      64  0.3536790               NA               NA               NA 1.424298
      65  0.3707512               NA               NA               NA 1.448823
      66  0.3547570               NA               NA               NA 1.425834
      67  0.3556460               NA               NA               NA 1.427102
      68  0.3465922               NA               NA               NA 1.414240
      69  0.3758430               NA               NA               NA 1.456218
      70  0.3856661               NA               NA               NA 1.470594
      71  0.3542125               NA               NA               NA 1.425058
      72  0.3593309               NA               NA               NA 1.432371
      73  0.3657925               NA               NA               NA 1.441656
      74  0.3611311               NA               NA               NA 1.434952
      75  0.3385130               NA               NA               NA 1.402860
      76  0.3738804               NA               NA               NA 1.453363
      77  0.3597065               NA               NA               NA 1.432909
      78  0.3612366               NA               NA               NA 1.435103
      79  0.3607899               NA               NA               NA 1.434462
      80  0.3609283               NA               NA               NA 1.434661
      81  0.3687189               NA               NA               NA 1.445881
      82  0.3664112               NA               NA               NA 1.442548
      83  0.3577425               NA               NA               NA 1.430097
      84  0.3577579               NA               NA               NA 1.430119
      85  0.3578947               NA               NA               NA 1.430315
      86  0.3629637               NA               NA               NA 1.437584
      87  0.3434041               NA               NA               NA 1.409738
      88  0.3523374               NA               NA               NA 1.422388
      89  0.3524220               NA               NA               NA 1.422509
      90  0.3642486               NA               NA               NA 1.439432
      91  0.3577968               NA               NA               NA 1.430175
      92  0.3492491               NA               NA               NA 1.418002
      93  0.3533376               NA               NA               NA 1.423812
      94  0.3530999               NA               NA               NA 1.423473
      95  0.3607553               NA               NA               NA 1.434412
      96  0.3721453               NA               NA               NA 1.450844
      97  0.3600291               NA               NA               NA 1.433371
      98  0.3676785               NA               NA               NA 1.444378
      99  0.3524318               NA               NA               NA 1.422523
      100 0.3438689               NA               NA               NA 1.410394
      
      $m4a$spM_lvlone
                            center       scale
      O1                        NA          NA
      C2               -0.06490582 0.333173465
      M2                        NA          NA
      O2                        NA          NA
      (Intercept)               NA          NA
      M22                       NA          NA
      M23                       NA          NA
      M24                       NA          NA
      O22                       NA          NA
      O23                       NA          NA
      O24                       NA          NA
      abs(C1 - C2)      1.49900534 0.334214181
      log(C1)           0.36049727 0.009050336
      O22:abs(C1 - C2)  0.31342466 0.618807150
      O23:abs(C1 - C2)  0.47068368 0.762352624
      O24:abs(C1 - C2)  0.40568706 0.692690317
      C1                1.43410054 0.012996511
      
      $m4a$mu_reg_norm
      [1] 0
      
      $m4a$tau_reg_norm
      [1] 1e-04
      
      $m4a$shape_tau_norm
      [1] 0.01
      
      $m4a$rate_tau_norm
      [1] 0.01
      
      $m4a$mu_reg_multinomial
      [1] 0
      
      $m4a$tau_reg_multinomial
      [1] 1e-04
      
      $m4a$mu_reg_ordinal
      [1] 0
      
      $m4a$tau_reg_ordinal
      [1] 1e-04
      
      $m4a$mu_delta_ordinal
      [1] 0
      
      $m4a$tau_delta_ordinal
      [1] 1e-04
      
      
      $m4b
      $m4b$M_lvlone
          O1           C2 O2 (Intercept)
      1    2  0.144065882  4           1
      2    4  0.032778478  4           1
      3    3  0.343008492  4           1
      4    2 -0.361887858  1           1
      5    3 -0.389600647  2           1
      6    1 -0.205306841  3           1
      7    3  0.079434830  4           1
      8    4 -0.331246757  2           1
      9    4 -0.329638800  4           1
      10   2  0.167597533  3           1
      11   1  0.860207989  2           1
      12   3  0.022730640  1           1
      13   3  0.217171172  1           1
      14   1 -0.403002412  1           1
      15   1  0.087369742  4           1
      16   4 -0.183870429  3           1
      17   2 -0.194577002  3           1
      18   3 -0.349718516  1           1
      19   4 -0.508781244  3           1
      20   1  0.494883111  1           1
      21   3  0.258041067  3           1
      22   4 -0.922621989  3           1
      23   4  0.431254949  2           1
      24   2 -0.294218881  3           1
      25   1 -0.425548895  2           1
      26   3  0.057176054  2           1
      27   4  0.289090158  1           1
      28   1 -0.473079489  4           1
      29   4 -0.385664863  3           1
      30   4 -0.154780107  3           1
      31   2  0.100536296  2           1
      32   3  0.634791958  2           1
      33   3 -0.387252617  1           1
      34   1 -0.181741088  1           1
      35   1 -0.311562695  4           1
      36   4 -0.044115907  3           1
      37   4 -0.657409991  3           1
      38   4  0.159577214  1           1
      39   1 -0.460416933  2           1
      40   2           NA  3           1
      41   1 -0.248909867  3           1
      42   1 -0.609021545  3           1
      43   2  0.025471883  3           1
      44   2  0.066648592  4           1
      45   1 -0.276108719  4           1
      46   1 -0.179737577  1           1
      47   4  0.181190937  4           1
      48   4 -0.453871693  4           1
      49   2  0.448629602  1           1
      50   2 -0.529811821  2           1
      51   1 -0.028304571  1           1
      52   3 -0.520318482  3           1
      53   1  0.171317619  2           1
      54   3  0.432732046  1           1
      55   2 -0.346286005  2           1
      56   4 -0.469375653  3           1
      57   2  0.031021711 NA           1
      58   1 -0.118837515  4           1
      59   1  0.507769984  4           1
      60   4  0.271797031  3           1
      61   2 -0.124442204  4           1
      62   4  0.277677389  1           1
      63   3 -0.102893730  4           1
      64   2           NA  4           1
      65   3 -0.678303052  4           1
      66   3  0.478880037  1           1
      67   2 -0.428028760  3           1
      68   1  0.048119185  3           1
      69   1  0.216932805  4           1
      70   1 -0.234575269  1           1
      71   1  0.006827078  4           1
      72   3 -0.456055171  4           1
      73   2  0.346486708  2           1
      74   2  0.205092215  4           1
      75   3 -0.136596858  3           1
      76   3 -0.500179043  2           1
      77   4  0.527352086  2           1
      78   3  0.022742250  3           1
      79   2           NA  2           1
      80   2 -0.002032440  1           1
      81   3 -0.154246160  4           1
      82   1  0.140201825  2           1
      83   3 -0.141417121  4           1
      84   2           NA  1           1
      85   2 -0.021285339  1           1
      86   4 -0.010196306  2           1
      87   3 -0.089747520  3           1
      88   2 -0.083699898  3           1
      89   3 -0.044061996  2           1
      90   3 -0.209291697  4           1
      91   4  0.639036426  2           1
      92   1  0.094698299  1           1
      93   4 -0.055510622 NA           1
      94   1 -0.421318463  3           1
      95   1  0.125295503  1           1
      96   3  0.213084904  3           1
      97   1 -0.161914659  2           1
      98   3 -0.034767685  2           1
      99   3 -0.320681689  4           1
      100  3  0.058192962  3           1
          ifelse(as.numeric(O2) > as.numeric(M1), 1, 0) abs(C1 - C2)   log(C1)
      1                                              NA           NA 0.3439662
      2                                              NA           NA 0.3605954
      3                                              NA           NA 0.3583696
      4                                              NA           NA 0.3736964
      5                                              NA           NA 0.3634928
      6                                              NA           NA 0.3737730
      7                                              NA           NA 0.3542952
      8                                              NA           NA 0.3631892
      9                                              NA           NA 0.3484794
      10                                             NA           NA 0.3706241
      11                                             NA           NA 0.3565373
      12                                             NA           NA 0.3716534
      13                                             NA           NA 0.3510408
      14                                             NA           NA 0.3527707
      15                                             NA           NA 0.3617934
      16                                             NA           NA 0.3534000
      17                                             NA           NA 0.3765220
      18                                             NA           NA 0.3466206
      19                                             NA           NA 0.3669896
      20                                             NA           NA 0.3611331
      21                                             NA           NA 0.3573242
      22                                             NA           NA 0.3659595
      23                                             NA           NA 0.3532680
      24                                             NA           NA 0.3614400
      25                                             NA           NA 0.3548341
      26                                             NA           NA 0.3626380
      27                                             NA           NA 0.3655634
      28                                             NA           NA 0.3527344
      29                                             NA           NA 0.3631120
      30                                             NA           NA 0.3867045
      31                                             NA           NA 0.3519109
      32                                             NA           NA 0.3768405
      33                                             NA           NA 0.3582630
      34                                             NA           NA 0.3587390
      35                                             NA           NA 0.3516387
      36                                             NA           NA 0.3608133
      37                                             NA           NA 0.3544406
      38                                             NA           NA 0.3519254
      39                                             NA           NA 0.3577404
      40                                             NA           NA 0.3699214
      41                                             NA           NA 0.3610235
      42                                             NA           NA 0.3688639
      43                                             NA           NA 0.3683210
      44                                             NA           NA 0.3707242
      45                                             NA           NA 0.3719890
      46                                             NA           NA 0.3471687
      47                                             NA           NA 0.3622725
      48                                             NA           NA 0.3604242
      49                                             NA           NA 0.3470878
      50                                             NA           NA 0.3519288
      51                                             NA           NA 0.3737703
      52                                             NA           NA 0.3730309
      53                                             NA           NA 0.3587298
      54                                             NA           NA 0.3577317
      55                                             NA           NA 0.3670651
      56                                             NA           NA 0.3621821
      57                                             NA           NA 0.3493310
      58                                             NA           NA 0.3611449
      59                                             NA           NA 0.3685236
      60                                             NA           NA 0.3626252
      61                                             NA           NA 0.3565271
      62                                             NA           NA 0.3650248
      63                                             NA           NA 0.3667342
      64                                             NA           NA 0.3536790
      65                                             NA           NA 0.3707512
      66                                             NA           NA 0.3547570
      67                                             NA           NA 0.3556460
      68                                             NA           NA 0.3465922
      69                                             NA           NA 0.3758430
      70                                             NA           NA 0.3856661
      71                                             NA           NA 0.3542125
      72                                             NA           NA 0.3593309
      73                                             NA           NA 0.3657925
      74                                             NA           NA 0.3611311
      75                                             NA           NA 0.3385130
      76                                             NA           NA 0.3738804
      77                                             NA           NA 0.3597065
      78                                             NA           NA 0.3612366
      79                                             NA           NA 0.3607899
      80                                             NA           NA 0.3609283
      81                                             NA           NA 0.3687189
      82                                             NA           NA 0.3664112
      83                                             NA           NA 0.3577425
      84                                             NA           NA 0.3577579
      85                                             NA           NA 0.3578947
      86                                             NA           NA 0.3629637
      87                                             NA           NA 0.3434041
      88                                             NA           NA 0.3523374
      89                                             NA           NA 0.3524220
      90                                             NA           NA 0.3642486
      91                                             NA           NA 0.3577968
      92                                             NA           NA 0.3492491
      93                                             NA           NA 0.3533376
      94                                             NA           NA 0.3530999
      95                                             NA           NA 0.3607553
      96                                             NA           NA 0.3721453
      97                                             NA           NA 0.3600291
      98                                             NA           NA 0.3676785
      99                                             NA           NA 0.3524318
      100                                            NA           NA 0.3438689
          ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2) O22 O23 O24 M12
      1                                                           NA  NA  NA  NA   0
      2                                                           NA  NA  NA  NA   1
      3                                                           NA  NA  NA  NA   1
      4                                                           NA  NA  NA  NA   0
      5                                                           NA  NA  NA  NA   0
      6                                                           NA  NA  NA  NA   0
      7                                                           NA  NA  NA  NA   0
      8                                                           NA  NA  NA  NA   0
      9                                                           NA  NA  NA  NA   0
      10                                                          NA  NA  NA  NA   1
      11                                                          NA  NA  NA  NA   0
      12                                                          NA  NA  NA  NA   1
      13                                                          NA  NA  NA  NA   0
      14                                                          NA  NA  NA  NA   0
      15                                                          NA  NA  NA  NA   1
      16                                                          NA  NA  NA  NA   0
      17                                                          NA  NA  NA  NA   0
      18                                                          NA  NA  NA  NA   0
      19                                                          NA  NA  NA  NA   1
      20                                                          NA  NA  NA  NA   1
      21                                                          NA  NA  NA  NA   0
      22                                                          NA  NA  NA  NA   0
      23                                                          NA  NA  NA  NA   0
      24                                                          NA  NA  NA  NA   1
      25                                                          NA  NA  NA  NA   0
      26                                                          NA  NA  NA  NA   0
      27                                                          NA  NA  NA  NA   1
      28                                                          NA  NA  NA  NA   0
      29                                                          NA  NA  NA  NA   0
      30                                                          NA  NA  NA  NA   0
      31                                                          NA  NA  NA  NA   0
      32                                                          NA  NA  NA  NA   0
      33                                                          NA  NA  NA  NA   0
      34                                                          NA  NA  NA  NA   1
      35                                                          NA  NA  NA  NA   0
      36                                                          NA  NA  NA  NA   0
      37                                                          NA  NA  NA  NA   0
      38                                                          NA  NA  NA  NA   1
      39                                                          NA  NA  NA  NA   1
      40                                                          NA  NA  NA  NA   1
      41                                                          NA  NA  NA  NA   0
      42                                                          NA  NA  NA  NA   0
      43                                                          NA  NA  NA  NA   0
      44                                                          NA  NA  NA  NA   0
      45                                                          NA  NA  NA  NA   1
      46                                                          NA  NA  NA  NA   0
      47                                                          NA  NA  NA  NA   0
      48                                                          NA  NA  NA  NA   0
      49                                                          NA  NA  NA  NA   1
      50                                                          NA  NA  NA  NA   1
      51                                                          NA  NA  NA  NA   0
      52                                                          NA  NA  NA  NA   0
      53                                                          NA  NA  NA  NA   1
      54                                                          NA  NA  NA  NA   0
      55                                                          NA  NA  NA  NA   1
      56                                                          NA  NA  NA  NA   0
      57                                                          NA  NA  NA  NA   0
      58                                                          NA  NA  NA  NA   0
      59                                                          NA  NA  NA  NA   0
      60                                                          NA  NA  NA  NA   0
      61                                                          NA  NA  NA  NA   0
      62                                                          NA  NA  NA  NA   0
      63                                                          NA  NA  NA  NA   0
      64                                                          NA  NA  NA  NA   0
      65                                                          NA  NA  NA  NA   1
      66                                                          NA  NA  NA  NA   0
      67                                                          NA  NA  NA  NA   0
      68                                                          NA  NA  NA  NA   0
      69                                                          NA  NA  NA  NA   0
      70                                                          NA  NA  NA  NA   1
      71                                                          NA  NA  NA  NA   0
      72                                                          NA  NA  NA  NA   1
      73                                                          NA  NA  NA  NA   0
      74                                                          NA  NA  NA  NA   1
      75                                                          NA  NA  NA  NA   0
      76                                                          NA  NA  NA  NA   0
      77                                                          NA  NA  NA  NA   1
      78                                                          NA  NA  NA  NA   0
      79                                                          NA  NA  NA  NA   0
      80                                                          NA  NA  NA  NA   0
      81                                                          NA  NA  NA  NA   0
      82                                                          NA  NA  NA  NA   0
      83                                                          NA  NA  NA  NA   0
      84                                                          NA  NA  NA  NA   0
      85                                                          NA  NA  NA  NA   1
      86                                                          NA  NA  NA  NA   0
      87                                                          NA  NA  NA  NA   0
      88                                                          NA  NA  NA  NA   0
      89                                                          NA  NA  NA  NA   0
      90                                                          NA  NA  NA  NA   0
      91                                                          NA  NA  NA  NA   0
      92                                                          NA  NA  NA  NA   0
      93                                                          NA  NA  NA  NA   0
      94                                                          NA  NA  NA  NA   0
      95                                                          NA  NA  NA  NA   1
      96                                                          NA  NA  NA  NA   0
      97                                                          NA  NA  NA  NA   0
      98                                                          NA  NA  NA  NA   0
      99                                                          NA  NA  NA  NA   1
      100                                                         NA  NA  NA  NA   0
          M13 M14       C1 M1
      1     0   0 1.410531  1
      2     0   0 1.434183  2
      3     0   0 1.430994  2
      4     0   0 1.453096  1
      5     1   0 1.438344  3
      6     1   0 1.453207  3
      7     1   0 1.425176  3
      8     1   0 1.437908  3
      9     0   0 1.416911  1
      10    0   0 1.448638  2
      11    0   0 1.428375  1
      12    0   0 1.450130  2
      13    0   0 1.420545  1
      14    0   1 1.423005  4
      15    0   0 1.435902  2
      16    1   0 1.423901  3
      17    1   0 1.457208  3
      18    0   0 1.414280  1
      19    0   0 1.443383  2
      20    0   0 1.434954  2
      21    0   0 1.429499  1
      22    0   1 1.441897  4
      23    0   0 1.423713  1
      24    0   0 1.435395  2
      25    0   0 1.425944  1
      26    0   0 1.437115  1
      27    0   0 1.441326  2
      28    0   0 1.422953  1
      29    1   0 1.437797  3
      30    0   0 1.472121  1
      31    0   1 1.421782  4
      32    0   0 1.457672  1
      33    0   1 1.430842  4
      34    0   0 1.431523  2
      35    0   0 1.421395  1
      36    0   0 1.434496  1
      37    0   0 1.425383  1
      38    0   0 1.421802  2
      39    0   0 1.430094  2
      40    0   0 1.447621  2
      41    0   1 1.434797  4
      42    0   1 1.446091  4
      43    0   1 1.445306  4
      44    0   1 1.448783  4
      45    0   0 1.450617  2
      46    0   0 1.415055  1
      47    1   0 1.436590  3
      48    1   0 1.433938  3
      49    0   0 1.414941  2
      50    0   0 1.421807  2
      51    1   0 1.453203  3
      52    0   0 1.452129  1
      53    0   0 1.431510  2
      54    1   0 1.430082  3
      55    0   0 1.443492  2
      56    0   0 1.436460  1
      57    0   1 1.418119  4
      58    0   0 1.434971  1
      59    0   1 1.445599  4
      60    0   0 1.437097  1
      61    0   0 1.428360  1
      62    0   0 1.440550  1
      63    0   1 1.443014  4
      64    0   0 1.424298  1
      65    0   0 1.448823  2
      66    0   1 1.425834  4
      67    0   1 1.427102  4
      68    1   0 1.414240  3
      69    1   0 1.456218  3
      70    0   0 1.470594  2
      71    1   0 1.425058  3
      72    0   0 1.432371  2
      73    0   1 1.441656  4
      74    0   0 1.434952  2
      75    0   0 1.402860  1
      76    1   0 1.453363  3
      77    0   0 1.432909  2
      78    0   1 1.435103  4
      79    0   1 1.434462  4
      80    0   0 1.434661  1
      81    0   0 1.445881  1
      82    0   1 1.442548  4
      83    1   0 1.430097  3
      84    0   1 1.430119  4
      85    0   0 1.430315  2
      86    0   1 1.437584  4
      87    1   0 1.409738  3
      88    1   0 1.422388  3
      89    1   0 1.422509  3
      90    0   0 1.439432  1
      91    0   0 1.430175  1
      92    0   0 1.418002  1
      93    0   0 1.423812  1
      94    1   0 1.423473  3
      95    0   0 1.434412  2
      96    0   0 1.450844  1
      97    1   0 1.433371  3
      98    0   1 1.444378  4
      99    0   0 1.422523  2
      100   0   0 1.410394  1
      
      $m4b$spM_lvlone
                                                                      center
      O1                                                                  NA
      C2                                                         -0.06490582
      O2                                                                  NA
      (Intercept)                                                         NA
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)               0.43877551
      abs(C1 - C2)                                                1.49900534
      log(C1)                                                     0.36049727
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)  0.65074863
      O22                                                                 NA
      O23                                                                 NA
      O24                                                                 NA
      M12                                                                 NA
      M13                                                                 NA
      M14                                                                 NA
      C1                                                          1.43410054
      M1                                                                  NA
                                                                       scale
      O1                                                                  NA
      C2                                                         0.333173465
      O2                                                                  NA
      (Intercept)                                                         NA
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)              0.498788771
      abs(C1 - C2)                                               0.334214181
      log(C1)                                                    0.009050336
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2) 0.780466974
      O22                                                                 NA
      O23                                                                 NA
      O24                                                                 NA
      M12                                                                 NA
      M13                                                                 NA
      M14                                                                 NA
      C1                                                         0.012996511
      M1                                                                  NA
      
      $m4b$mu_reg_norm
      [1] 0
      
      $m4b$tau_reg_norm
      [1] 1e-04
      
      $m4b$shape_tau_norm
      [1] 0.01
      
      $m4b$rate_tau_norm
      [1] 0.01
      
      $m4b$mu_reg_ordinal
      [1] 0
      
      $m4b$tau_reg_ordinal
      [1] 1e-04
      
      $m4b$mu_delta_ordinal
      [1] 0
      
      $m4b$tau_delta_ordinal
      [1] 1e-04
      
      
      $m5a
      $m5a$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA
      
      $m5a$spM_lvlone
                       center      scale
      O1                   NA         NA
      C2          -0.06490582 0.33317347
      M2                   NA         NA
      O2                   NA         NA
      (Intercept)          NA         NA
      C1           1.43410054 0.01299651
      M22                  NA         NA
      M23                  NA         NA
      M24                  NA         NA
      O22                  NA         NA
      O23                  NA         NA
      O24                  NA         NA
      
      $m5a$mu_reg_norm
      [1] 0
      
      $m5a$tau_reg_norm
      [1] 1e-04
      
      $m5a$shape_tau_norm
      [1] 0.01
      
      $m5a$rate_tau_norm
      [1] 0.01
      
      $m5a$mu_reg_multinomial
      [1] 0
      
      $m5a$tau_reg_multinomial
      [1] 1e-04
      
      $m5a$mu_reg_ordinal
      [1] 0
      
      $m5a$tau_reg_ordinal
      [1] 1e-04
      
      $m5a$mu_delta_ordinal
      [1] 0
      
      $m5a$tau_delta_ordinal
      [1] 1e-04
      
      
      $m5b
      $m5b$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24 C1:C2
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA    NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA    NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA    NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA    NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA    NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA    NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA    NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA    NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA    NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA    NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA    NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA    NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA    NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA    NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA    NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA    NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA    NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA    NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA    NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA    NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA    NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA    NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA    NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA    NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA    NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA    NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA    NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA    NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA    NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA    NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA    NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA    NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA    NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA    NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA    NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA    NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA    NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA    NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA    NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA    NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA    NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA    NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA    NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA    NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA    NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA    NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA    NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA    NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA    NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA    NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA    NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA    NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA    NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA    NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA    NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA    NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA    NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA    NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA    NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA    NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA    NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA    NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA    NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA    NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA    NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA    NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA    NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA    NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA    NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA    NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA    NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA    NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA    NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA    NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA    NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA    NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA    NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA    NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA    NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA    NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA    NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA    NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA    NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA    NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA    NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA    NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA    NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA    NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA    NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA    NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA    NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA    NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA    NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA    NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA    NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA    NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA    NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA    NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA    NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA    NA
      
      $m5b$spM_lvlone
                       center      scale
      O1                   NA         NA
      C2          -0.06490582 0.33317347
      M2                   NA         NA
      O2                   NA         NA
      (Intercept)          NA         NA
      C1           1.43410054 0.01299651
      M22                  NA         NA
      M23                  NA         NA
      M24                  NA         NA
      O22                  NA         NA
      O23                  NA         NA
      O24                  NA         NA
      C1:C2       -0.09333951 0.47826999
      
      $m5b$mu_reg_norm
      [1] 0
      
      $m5b$tau_reg_norm
      [1] 1e-04
      
      $m5b$shape_tau_norm
      [1] 0.01
      
      $m5b$rate_tau_norm
      [1] 0.01
      
      $m5b$mu_reg_multinomial
      [1] 0
      
      $m5b$tau_reg_multinomial
      [1] 1e-04
      
      $m5b$mu_reg_ordinal
      [1] 0
      
      $m5b$tau_reg_ordinal
      [1] 1e-04
      
      $m5b$mu_delta_ordinal
      [1] 0
      
      $m5b$tau_delta_ordinal
      [1] 1e-04
      
      
      $m5c
      $m5c$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24 C1:C2
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA    NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA    NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA    NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA    NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA    NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA    NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA    NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA    NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA    NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA    NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA    NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA    NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA    NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA    NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA    NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA    NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA    NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA    NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA    NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA    NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA    NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA    NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA    NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA    NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA    NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA    NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA    NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA    NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA    NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA    NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA    NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA    NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA    NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA    NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA    NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA    NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA    NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA    NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA    NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA    NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA    NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA    NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA    NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA    NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA    NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA    NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA    NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA    NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA    NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA    NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA    NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA    NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA    NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA    NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA    NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA    NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA    NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA    NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA    NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA    NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA    NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA    NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA    NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA    NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA    NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA    NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA    NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA    NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA    NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA    NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA    NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA    NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA    NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA    NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA    NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA    NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA    NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA    NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA    NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA    NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA    NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA    NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA    NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA    NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA    NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA    NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA    NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA    NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA    NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA    NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA    NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA    NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA    NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA    NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA    NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA    NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA    NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA    NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA    NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA    NA
      
      $m5c$spM_lvlone
                       center      scale
      O1                   NA         NA
      C2          -0.06490582 0.33317347
      M2                   NA         NA
      O2                   NA         NA
      (Intercept)          NA         NA
      C1           1.43410054 0.01299651
      M22                  NA         NA
      M23                  NA         NA
      M24                  NA         NA
      O22                  NA         NA
      O23                  NA         NA
      O24                  NA         NA
      C1:C2       -0.09333951 0.47826999
      
      $m5c$mu_reg_norm
      [1] 0
      
      $m5c$tau_reg_norm
      [1] 1e-04
      
      $m5c$shape_tau_norm
      [1] 0.01
      
      $m5c$rate_tau_norm
      [1] 0.01
      
      $m5c$mu_reg_multinomial
      [1] 0
      
      $m5c$tau_reg_multinomial
      [1] 1e-04
      
      $m5c$mu_reg_ordinal
      [1] 0
      
      $m5c$tau_reg_ordinal
      [1] 1e-04
      
      $m5c$mu_delta_ordinal
      [1] 0
      
      $m5c$tau_delta_ordinal
      [1] 1e-04
      
      
      $m5d
      $m5d$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24 M22:C2
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA     NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA     NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA     NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA     NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA     NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA     NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA     NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA     NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA     NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA     NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA     NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA     NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA     NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA     NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA     NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA     NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA     NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA     NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA     NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA     NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA     NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA     NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA     NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA     NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA     NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA     NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA     NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA     NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA     NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA     NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA     NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA     NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA     NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA     NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA     NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA     NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA     NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA     NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA     NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA     NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA     NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA     NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA     NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA     NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA     NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA     NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA     NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA     NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA     NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA     NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA     NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA     NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA     NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA     NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA     NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA     NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA     NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA     NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA     NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA     NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA     NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA     NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA     NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA     NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA     NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA     NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA     NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA     NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA     NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA     NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA     NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA     NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA     NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA     NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA     NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA     NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA     NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA     NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA     NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA     NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA     NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA     NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA     NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA     NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA     NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA     NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA     NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA     NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA     NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA     NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA     NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA     NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA     NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA     NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA     NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA     NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA     NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA     NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA     NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA     NA
          M23:C2 M24:C2
      1       NA     NA
      2       NA     NA
      3       NA     NA
      4       NA     NA
      5       NA     NA
      6       NA     NA
      7       NA     NA
      8       NA     NA
      9       NA     NA
      10      NA     NA
      11      NA     NA
      12      NA     NA
      13      NA     NA
      14      NA     NA
      15      NA     NA
      16      NA     NA
      17      NA     NA
      18      NA     NA
      19      NA     NA
      20      NA     NA
      21      NA     NA
      22      NA     NA
      23      NA     NA
      24      NA     NA
      25      NA     NA
      26      NA     NA
      27      NA     NA
      28      NA     NA
      29      NA     NA
      30      NA     NA
      31      NA     NA
      32      NA     NA
      33      NA     NA
      34      NA     NA
      35      NA     NA
      36      NA     NA
      37      NA     NA
      38      NA     NA
      39      NA     NA
      40      NA     NA
      41      NA     NA
      42      NA     NA
      43      NA     NA
      44      NA     NA
      45      NA     NA
      46      NA     NA
      47      NA     NA
      48      NA     NA
      49      NA     NA
      50      NA     NA
      51      NA     NA
      52      NA     NA
      53      NA     NA
      54      NA     NA
      55      NA     NA
      56      NA     NA
      57      NA     NA
      58      NA     NA
      59      NA     NA
      60      NA     NA
      61      NA     NA
      62      NA     NA
      63      NA     NA
      64      NA     NA
      65      NA     NA
      66      NA     NA
      67      NA     NA
      68      NA     NA
      69      NA     NA
      70      NA     NA
      71      NA     NA
      72      NA     NA
      73      NA     NA
      74      NA     NA
      75      NA     NA
      76      NA     NA
      77      NA     NA
      78      NA     NA
      79      NA     NA
      80      NA     NA
      81      NA     NA
      82      NA     NA
      83      NA     NA
      84      NA     NA
      85      NA     NA
      86      NA     NA
      87      NA     NA
      88      NA     NA
      89      NA     NA
      90      NA     NA
      91      NA     NA
      92      NA     NA
      93      NA     NA
      94      NA     NA
      95      NA     NA
      96      NA     NA
      97      NA     NA
      98      NA     NA
      99      NA     NA
      100     NA     NA
      
      $m5d$spM_lvlone
                        center      scale
      O1                    NA         NA
      C2          -0.064905817 0.33317347
      M2                    NA         NA
      O2                    NA         NA
      (Intercept)           NA         NA
      C1           1.434100545 0.01299651
      M22                   NA         NA
      M23                   NA         NA
      M24                   NA         NA
      O22                   NA         NA
      O23                   NA         NA
      O24                   NA         NA
      M22:C2      -0.035803577 0.16299962
      M23:C2      -0.008443652 0.22326710
      M24:C2      -0.014114090 0.17029222
      
      $m5d$mu_reg_norm
      [1] 0
      
      $m5d$tau_reg_norm
      [1] 1e-04
      
      $m5d$shape_tau_norm
      [1] 0.01
      
      $m5d$rate_tau_norm
      [1] 0.01
      
      $m5d$mu_reg_multinomial
      [1] 0
      
      $m5d$tau_reg_multinomial
      [1] 1e-04
      
      $m5d$mu_reg_ordinal
      [1] 0
      
      $m5d$tau_reg_ordinal
      [1] 1e-04
      
      $m5d$mu_delta_ordinal
      [1] 0
      
      $m5d$tau_delta_ordinal
      [1] 1e-04
      
      
      $m5e
      $m5e$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24 M22:C2
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA     NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA     NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA     NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA     NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA     NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA     NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA     NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA     NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA     NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA     NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA     NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA     NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA     NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA     NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA     NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA     NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA     NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA     NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA     NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA     NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA     NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA     NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA     NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA     NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA     NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA     NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA     NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA     NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA     NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA     NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA     NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA     NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA     NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA     NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA     NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA     NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA     NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA     NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA     NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA     NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA     NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA     NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA     NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA     NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA     NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA     NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA     NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA     NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA     NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA     NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA     NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA     NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA     NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA     NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA     NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA     NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA     NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA     NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA     NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA     NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA     NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA     NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA     NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA     NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA     NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA     NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA     NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA     NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA     NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA     NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA     NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA     NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA     NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA     NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA     NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA     NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA     NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA     NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA     NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA     NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA     NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA     NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA     NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA     NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA     NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA     NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA     NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA     NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA     NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA     NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA     NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA     NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA     NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA     NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA     NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA     NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA     NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA     NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA     NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA     NA
          M23:C2 M24:C2
      1       NA     NA
      2       NA     NA
      3       NA     NA
      4       NA     NA
      5       NA     NA
      6       NA     NA
      7       NA     NA
      8       NA     NA
      9       NA     NA
      10      NA     NA
      11      NA     NA
      12      NA     NA
      13      NA     NA
      14      NA     NA
      15      NA     NA
      16      NA     NA
      17      NA     NA
      18      NA     NA
      19      NA     NA
      20      NA     NA
      21      NA     NA
      22      NA     NA
      23      NA     NA
      24      NA     NA
      25      NA     NA
      26      NA     NA
      27      NA     NA
      28      NA     NA
      29      NA     NA
      30      NA     NA
      31      NA     NA
      32      NA     NA
      33      NA     NA
      34      NA     NA
      35      NA     NA
      36      NA     NA
      37      NA     NA
      38      NA     NA
      39      NA     NA
      40      NA     NA
      41      NA     NA
      42      NA     NA
      43      NA     NA
      44      NA     NA
      45      NA     NA
      46      NA     NA
      47      NA     NA
      48      NA     NA
      49      NA     NA
      50      NA     NA
      51      NA     NA
      52      NA     NA
      53      NA     NA
      54      NA     NA
      55      NA     NA
      56      NA     NA
      57      NA     NA
      58      NA     NA
      59      NA     NA
      60      NA     NA
      61      NA     NA
      62      NA     NA
      63      NA     NA
      64      NA     NA
      65      NA     NA
      66      NA     NA
      67      NA     NA
      68      NA     NA
      69      NA     NA
      70      NA     NA
      71      NA     NA
      72      NA     NA
      73      NA     NA
      74      NA     NA
      75      NA     NA
      76      NA     NA
      77      NA     NA
      78      NA     NA
      79      NA     NA
      80      NA     NA
      81      NA     NA
      82      NA     NA
      83      NA     NA
      84      NA     NA
      85      NA     NA
      86      NA     NA
      87      NA     NA
      88      NA     NA
      89      NA     NA
      90      NA     NA
      91      NA     NA
      92      NA     NA
      93      NA     NA
      94      NA     NA
      95      NA     NA
      96      NA     NA
      97      NA     NA
      98      NA     NA
      99      NA     NA
      100     NA     NA
      
      $m5e$spM_lvlone
                        center      scale
      O1                    NA         NA
      C2          -0.064905817 0.33317347
      M2                    NA         NA
      O2                    NA         NA
      (Intercept)           NA         NA
      C1           1.434100545 0.01299651
      M22                   NA         NA
      M23                   NA         NA
      M24                   NA         NA
      O22                   NA         NA
      O23                   NA         NA
      O24                   NA         NA
      M22:C2      -0.035803577 0.16299962
      M23:C2      -0.008443652 0.22326710
      M24:C2      -0.014114090 0.17029222
      
      $m5e$mu_reg_norm
      [1] 0
      
      $m5e$tau_reg_norm
      [1] 1e-04
      
      $m5e$shape_tau_norm
      [1] 0.01
      
      $m5e$rate_tau_norm
      [1] 0.01
      
      $m5e$mu_reg_multinomial
      [1] 0
      
      $m5e$tau_reg_multinomial
      [1] 1e-04
      
      $m5e$mu_reg_ordinal
      [1] 0
      
      $m5e$tau_reg_ordinal
      [1] 1e-04
      
      $m5e$mu_delta_ordinal
      [1] 0
      
      $m5e$tau_delta_ordinal
      [1] 1e-04
      
      
      $m6a
      $m6a$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA
      
      $m6a$spM_lvlone
                       center      scale
      O1                   NA         NA
      C2          -0.06490582 0.33317347
      M2                   NA         NA
      O2                   NA         NA
      (Intercept)          NA         NA
      C1           1.43410054 0.01299651
      M22                  NA         NA
      M23                  NA         NA
      M24                  NA         NA
      O22                  NA         NA
      O23                  NA         NA
      O24                  NA         NA
      
      $m6a$mu_reg_norm
      [1] 0
      
      $m6a$tau_reg_norm
      [1] 1e-04
      
      $m6a$shape_tau_norm
      [1] 0.01
      
      $m6a$rate_tau_norm
      [1] 0.01
      
      $m6a$mu_reg_multinomial
      [1] 0
      
      $m6a$tau_reg_multinomial
      [1] 1e-04
      
      $m6a$mu_reg_ordinal
      [1] 0
      
      $m6a$tau_reg_ordinal
      [1] 1e-04
      
      $m6a$mu_delta_ordinal
      [1] 0
      
      $m6a$tau_delta_ordinal
      [1] 1e-04
      
      
      $m6b
      $m6b$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24 C1:C2
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA    NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA    NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA    NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA    NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA    NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA    NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA    NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA    NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA    NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA    NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA    NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA    NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA    NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA    NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA    NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA    NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA    NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA    NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA    NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA    NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA    NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA    NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA    NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA    NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA    NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA    NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA    NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA    NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA    NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA    NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA    NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA    NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA    NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA    NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA    NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA    NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA    NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA    NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA    NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA    NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA    NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA    NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA    NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA    NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA    NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA    NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA    NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA    NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA    NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA    NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA    NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA    NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA    NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA    NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA    NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA    NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA    NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA    NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA    NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA    NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA    NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA    NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA    NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA    NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA    NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA    NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA    NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA    NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA    NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA    NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA    NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA    NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA    NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA    NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA    NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA    NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA    NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA    NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA    NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA    NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA    NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA    NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA    NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA    NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA    NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA    NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA    NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA    NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA    NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA    NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA    NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA    NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA    NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA    NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA    NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA    NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA    NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA    NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA    NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA    NA
      
      $m6b$spM_lvlone
                       center      scale
      O1                   NA         NA
      C2          -0.06490582 0.33317347
      M2                   NA         NA
      O2                   NA         NA
      (Intercept)          NA         NA
      C1           1.43410054 0.01299651
      M22                  NA         NA
      M23                  NA         NA
      M24                  NA         NA
      O22                  NA         NA
      O23                  NA         NA
      O24                  NA         NA
      C1:C2       -0.09333951 0.47826999
      
      $m6b$mu_reg_norm
      [1] 0
      
      $m6b$tau_reg_norm
      [1] 1e-04
      
      $m6b$shape_tau_norm
      [1] 0.01
      
      $m6b$rate_tau_norm
      [1] 0.01
      
      $m6b$mu_reg_multinomial
      [1] 0
      
      $m6b$tau_reg_multinomial
      [1] 1e-04
      
      $m6b$mu_reg_ordinal
      [1] 0
      
      $m6b$tau_reg_ordinal
      [1] 1e-04
      
      $m6b$mu_delta_ordinal
      [1] 0
      
      $m6b$tau_delta_ordinal
      [1] 1e-04
      
      
      $m6c
      $m6c$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24 C1:C2
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA    NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA    NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA    NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA    NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA    NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA    NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA    NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA    NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA    NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA    NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA    NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA    NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA    NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA    NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA    NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA    NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA    NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA    NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA    NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA    NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA    NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA    NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA    NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA    NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA    NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA    NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA    NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA    NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA    NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA    NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA    NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA    NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA    NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA    NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA    NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA    NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA    NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA    NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA    NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA    NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA    NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA    NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA    NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA    NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA    NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA    NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA    NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA    NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA    NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA    NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA    NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA    NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA    NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA    NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA    NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA    NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA    NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA    NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA    NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA    NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA    NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA    NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA    NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA    NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA    NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA    NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA    NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA    NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA    NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA    NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA    NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA    NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA    NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA    NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA    NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA    NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA    NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA    NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA    NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA    NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA    NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA    NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA    NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA    NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA    NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA    NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA    NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA    NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA    NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA    NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA    NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA    NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA    NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA    NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA    NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA    NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA    NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA    NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA    NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA    NA
      
      $m6c$spM_lvlone
                       center      scale
      O1                   NA         NA
      C2          -0.06490582 0.33317347
      M2                   NA         NA
      O2                   NA         NA
      (Intercept)          NA         NA
      C1           1.43410054 0.01299651
      M22                  NA         NA
      M23                  NA         NA
      M24                  NA         NA
      O22                  NA         NA
      O23                  NA         NA
      O24                  NA         NA
      C1:C2       -0.09333951 0.47826999
      
      $m6c$mu_reg_norm
      [1] 0
      
      $m6c$tau_reg_norm
      [1] 1e-04
      
      $m6c$shape_tau_norm
      [1] 0.01
      
      $m6c$rate_tau_norm
      [1] 0.01
      
      $m6c$mu_reg_multinomial
      [1] 0
      
      $m6c$tau_reg_multinomial
      [1] 1e-04
      
      $m6c$mu_reg_ordinal
      [1] 0
      
      $m6c$tau_reg_ordinal
      [1] 1e-04
      
      $m6c$mu_delta_ordinal
      [1] 0
      
      $m6c$tau_delta_ordinal
      [1] 1e-04
      
      
      $m6d
      $m6d$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24 M22:C2
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA     NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA     NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA     NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA     NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA     NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA     NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA     NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA     NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA     NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA     NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA     NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA     NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA     NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA     NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA     NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA     NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA     NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA     NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA     NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA     NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA     NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA     NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA     NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA     NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA     NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA     NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA     NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA     NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA     NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA     NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA     NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA     NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA     NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA     NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA     NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA     NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA     NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA     NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA     NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA     NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA     NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA     NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA     NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA     NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA     NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA     NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA     NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA     NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA     NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA     NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA     NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA     NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA     NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA     NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA     NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA     NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA     NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA     NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA     NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA     NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA     NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA     NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA     NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA     NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA     NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA     NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA     NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA     NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA     NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA     NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA     NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA     NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA     NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA     NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA     NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA     NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA     NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA     NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA     NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA     NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA     NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA     NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA     NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA     NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA     NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA     NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA     NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA     NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA     NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA     NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA     NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA     NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA     NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA     NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA     NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA     NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA     NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA     NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA     NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA     NA
          M23:C2 M24:C2
      1       NA     NA
      2       NA     NA
      3       NA     NA
      4       NA     NA
      5       NA     NA
      6       NA     NA
      7       NA     NA
      8       NA     NA
      9       NA     NA
      10      NA     NA
      11      NA     NA
      12      NA     NA
      13      NA     NA
      14      NA     NA
      15      NA     NA
      16      NA     NA
      17      NA     NA
      18      NA     NA
      19      NA     NA
      20      NA     NA
      21      NA     NA
      22      NA     NA
      23      NA     NA
      24      NA     NA
      25      NA     NA
      26      NA     NA
      27      NA     NA
      28      NA     NA
      29      NA     NA
      30      NA     NA
      31      NA     NA
      32      NA     NA
      33      NA     NA
      34      NA     NA
      35      NA     NA
      36      NA     NA
      37      NA     NA
      38      NA     NA
      39      NA     NA
      40      NA     NA
      41      NA     NA
      42      NA     NA
      43      NA     NA
      44      NA     NA
      45      NA     NA
      46      NA     NA
      47      NA     NA
      48      NA     NA
      49      NA     NA
      50      NA     NA
      51      NA     NA
      52      NA     NA
      53      NA     NA
      54      NA     NA
      55      NA     NA
      56      NA     NA
      57      NA     NA
      58      NA     NA
      59      NA     NA
      60      NA     NA
      61      NA     NA
      62      NA     NA
      63      NA     NA
      64      NA     NA
      65      NA     NA
      66      NA     NA
      67      NA     NA
      68      NA     NA
      69      NA     NA
      70      NA     NA
      71      NA     NA
      72      NA     NA
      73      NA     NA
      74      NA     NA
      75      NA     NA
      76      NA     NA
      77      NA     NA
      78      NA     NA
      79      NA     NA
      80      NA     NA
      81      NA     NA
      82      NA     NA
      83      NA     NA
      84      NA     NA
      85      NA     NA
      86      NA     NA
      87      NA     NA
      88      NA     NA
      89      NA     NA
      90      NA     NA
      91      NA     NA
      92      NA     NA
      93      NA     NA
      94      NA     NA
      95      NA     NA
      96      NA     NA
      97      NA     NA
      98      NA     NA
      99      NA     NA
      100     NA     NA
      
      $m6d$spM_lvlone
                        center      scale
      O1                    NA         NA
      C2          -0.064905817 0.33317347
      M2                    NA         NA
      O2                    NA         NA
      (Intercept)           NA         NA
      C1           1.434100545 0.01299651
      M22                   NA         NA
      M23                   NA         NA
      M24                   NA         NA
      O22                   NA         NA
      O23                   NA         NA
      O24                   NA         NA
      M22:C2      -0.035803577 0.16299962
      M23:C2      -0.008443652 0.22326710
      M24:C2      -0.014114090 0.17029222
      
      $m6d$mu_reg_norm
      [1] 0
      
      $m6d$tau_reg_norm
      [1] 1e-04
      
      $m6d$shape_tau_norm
      [1] 0.01
      
      $m6d$rate_tau_norm
      [1] 0.01
      
      $m6d$mu_reg_multinomial
      [1] 0
      
      $m6d$tau_reg_multinomial
      [1] 1e-04
      
      $m6d$mu_reg_ordinal
      [1] 0
      
      $m6d$tau_reg_ordinal
      [1] 1e-04
      
      $m6d$mu_delta_ordinal
      [1] 0
      
      $m6d$tau_delta_ordinal
      [1] 1e-04
      
      
      $m6e
      $m6e$M_lvlone
          O1           C2 M2 O2 (Intercept)       C1 M22 M23 M24 O22 O23 O24 M22:C2
      1    2  0.144065882  4  4           1 1.410531  NA  NA  NA  NA  NA  NA     NA
      2    4  0.032778478  1  4           1 1.434183  NA  NA  NA  NA  NA  NA     NA
      3    3  0.343008492  3  4           1 1.430994  NA  NA  NA  NA  NA  NA     NA
      4    2 -0.361887858  3  1           1 1.453096  NA  NA  NA  NA  NA  NA     NA
      5    3 -0.389600647  4  2           1 1.438344  NA  NA  NA  NA  NA  NA     NA
      6    1 -0.205306841  4  3           1 1.453207  NA  NA  NA  NA  NA  NA     NA
      7    3  0.079434830  1  4           1 1.425176  NA  NA  NA  NA  NA  NA     NA
      8    4 -0.331246757  1  2           1 1.437908  NA  NA  NA  NA  NA  NA     NA
      9    4 -0.329638800  2  4           1 1.416911  NA  NA  NA  NA  NA  NA     NA
      10   2  0.167597533  2  3           1 1.448638  NA  NA  NA  NA  NA  NA     NA
      11   1  0.860207989  3  2           1 1.428375  NA  NA  NA  NA  NA  NA     NA
      12   3  0.022730640  3  1           1 1.450130  NA  NA  NA  NA  NA  NA     NA
      13   3  0.217171172  2  1           1 1.420545  NA  NA  NA  NA  NA  NA     NA
      14   1 -0.403002412  3  1           1 1.423005  NA  NA  NA  NA  NA  NA     NA
      15   1  0.087369742  2  4           1 1.435902  NA  NA  NA  NA  NA  NA     NA
      16   4 -0.183870429  1  3           1 1.423901  NA  NA  NA  NA  NA  NA     NA
      17   2 -0.194577002  4  3           1 1.457208  NA  NA  NA  NA  NA  NA     NA
      18   3 -0.349718516  2  1           1 1.414280  NA  NA  NA  NA  NA  NA     NA
      19   4 -0.508781244  3  3           1 1.443383  NA  NA  NA  NA  NA  NA     NA
      20   1  0.494883111  3  1           1 1.434954  NA  NA  NA  NA  NA  NA     NA
      21   3  0.258041067  2  3           1 1.429499  NA  NA  NA  NA  NA  NA     NA
      22   4 -0.922621989  2  3           1 1.441897  NA  NA  NA  NA  NA  NA     NA
      23   4  0.431254949  3  2           1 1.423713  NA  NA  NA  NA  NA  NA     NA
      24   2 -0.294218881  3  3           1 1.435395  NA  NA  NA  NA  NA  NA     NA
      25   1 -0.425548895  2  2           1 1.425944  NA  NA  NA  NA  NA  NA     NA
      26   3  0.057176054  2  2           1 1.437115  NA  NA  NA  NA  NA  NA     NA
      27   4  0.289090158  1  1           1 1.441326  NA  NA  NA  NA  NA  NA     NA
      28   1 -0.473079489  3  4           1 1.422953  NA  NA  NA  NA  NA  NA     NA
      29   4 -0.385664863  4  3           1 1.437797  NA  NA  NA  NA  NA  NA     NA
      30   4 -0.154780107  2  3           1 1.472121  NA  NA  NA  NA  NA  NA     NA
      31   2  0.100536296 NA  2           1 1.421782  NA  NA  NA  NA  NA  NA     NA
      32   3  0.634791958  4  2           1 1.457672  NA  NA  NA  NA  NA  NA     NA
      33   3 -0.387252617  4  1           1 1.430842  NA  NA  NA  NA  NA  NA     NA
      34   1 -0.181741088  4  1           1 1.431523  NA  NA  NA  NA  NA  NA     NA
      35   1 -0.311562695  2  4           1 1.421395  NA  NA  NA  NA  NA  NA     NA
      36   4 -0.044115907  1  3           1 1.434496  NA  NA  NA  NA  NA  NA     NA
      37   4 -0.657409991  3  3           1 1.425383  NA  NA  NA  NA  NA  NA     NA
      38   4  0.159577214  4  1           1 1.421802  NA  NA  NA  NA  NA  NA     NA
      39   1 -0.460416933  3  2           1 1.430094  NA  NA  NA  NA  NA  NA     NA
      40   2           NA  3  3           1 1.447621  NA  NA  NA  NA  NA  NA     NA
      41   1 -0.248909867  1  3           1 1.434797  NA  NA  NA  NA  NA  NA     NA
      42   1 -0.609021545  4  3           1 1.446091  NA  NA  NA  NA  NA  NA     NA
      43   2  0.025471883  1  3           1 1.445306  NA  NA  NA  NA  NA  NA     NA
      44   2  0.066648592  2  4           1 1.448783  NA  NA  NA  NA  NA  NA     NA
      45   1 -0.276108719  2  4           1 1.450617  NA  NA  NA  NA  NA  NA     NA
      46   1 -0.179737577  1  1           1 1.415055  NA  NA  NA  NA  NA  NA     NA
      47   4  0.181190937  4  4           1 1.436590  NA  NA  NA  NA  NA  NA     NA
      48   4 -0.453871693  2  4           1 1.433938  NA  NA  NA  NA  NA  NA     NA
      49   2  0.448629602  4  1           1 1.414941  NA  NA  NA  NA  NA  NA     NA
      50   2 -0.529811821  1  2           1 1.421807  NA  NA  NA  NA  NA  NA     NA
      51   1 -0.028304571  4  1           1 1.453203  NA  NA  NA  NA  NA  NA     NA
      52   3 -0.520318482  4  3           1 1.452129  NA  NA  NA  NA  NA  NA     NA
      53   1  0.171317619  4  2           1 1.431510  NA  NA  NA  NA  NA  NA     NA
      54   3  0.432732046  3  1           1 1.430082  NA  NA  NA  NA  NA  NA     NA
      55   2 -0.346286005  3  2           1 1.443492  NA  NA  NA  NA  NA  NA     NA
      56   4 -0.469375653  3  3           1 1.436460  NA  NA  NA  NA  NA  NA     NA
      57   2  0.031021711  2 NA           1 1.418119  NA  NA  NA  NA  NA  NA     NA
      58   1 -0.118837515  3  4           1 1.434971  NA  NA  NA  NA  NA  NA     NA
      59   1  0.507769984  3  4           1 1.445599  NA  NA  NA  NA  NA  NA     NA
      60   4  0.271797031  4  3           1 1.437097  NA  NA  NA  NA  NA  NA     NA
      61   2 -0.124442204  2  4           1 1.428360  NA  NA  NA  NA  NA  NA     NA
      62   4  0.277677389  2  1           1 1.440550  NA  NA  NA  NA  NA  NA     NA
      63   3 -0.102893730  1  4           1 1.443014  NA  NA  NA  NA  NA  NA     NA
      64   2           NA  2  4           1 1.424298  NA  NA  NA  NA  NA  NA     NA
      65   3 -0.678303052  2  4           1 1.448823  NA  NA  NA  NA  NA  NA     NA
      66   3  0.478880037  3  1           1 1.425834  NA  NA  NA  NA  NA  NA     NA
      67   2 -0.428028760  2  3           1 1.427102  NA  NA  NA  NA  NA  NA     NA
      68   1  0.048119185  4  3           1 1.414240  NA  NA  NA  NA  NA  NA     NA
      69   1  0.216932805 NA  4           1 1.456218  NA  NA  NA  NA  NA  NA     NA
      70   1 -0.234575269  1  1           1 1.470594  NA  NA  NA  NA  NA  NA     NA
      71   1  0.006827078  2  4           1 1.425058  NA  NA  NA  NA  NA  NA     NA
      72   3 -0.456055171  3  4           1 1.432371  NA  NA  NA  NA  NA  NA     NA
      73   2  0.346486708  4  2           1 1.441656  NA  NA  NA  NA  NA  NA     NA
      74   2  0.205092215  4  4           1 1.434952  NA  NA  NA  NA  NA  NA     NA
      75   3 -0.136596858  1  3           1 1.402860  NA  NA  NA  NA  NA  NA     NA
      76   3 -0.500179043  4  2           1 1.453363  NA  NA  NA  NA  NA  NA     NA
      77   4  0.527352086 NA  2           1 1.432909  NA  NA  NA  NA  NA  NA     NA
      78   3  0.022742250  2  3           1 1.435103  NA  NA  NA  NA  NA  NA     NA
      79   2           NA  2  2           1 1.434462  NA  NA  NA  NA  NA  NA     NA
      80   2 -0.002032440  2  1           1 1.434661  NA  NA  NA  NA  NA  NA     NA
      81   3 -0.154246160  4  4           1 1.445881  NA  NA  NA  NA  NA  NA     NA
      82   1  0.140201825  3  2           1 1.442548  NA  NA  NA  NA  NA  NA     NA
      83   3 -0.141417121  3  4           1 1.430097  NA  NA  NA  NA  NA  NA     NA
      84   2           NA  1  1           1 1.430119  NA  NA  NA  NA  NA  NA     NA
      85   2 -0.021285339  2  1           1 1.430315  NA  NA  NA  NA  NA  NA     NA
      86   4 -0.010196306  1  2           1 1.437584  NA  NA  NA  NA  NA  NA     NA
      87   3 -0.089747520  3  3           1 1.409738  NA  NA  NA  NA  NA  NA     NA
      88   2 -0.083699898  1  3           1 1.422388  NA  NA  NA  NA  NA  NA     NA
      89   3 -0.044061996  2  2           1 1.422509  NA  NA  NA  NA  NA  NA     NA
      90   3 -0.209291697  1  4           1 1.439432  NA  NA  NA  NA  NA  NA     NA
      91   4  0.639036426  3  2           1 1.430175  NA  NA  NA  NA  NA  NA     NA
      92   1  0.094698299  1  1           1 1.418002  NA  NA  NA  NA  NA  NA     NA
      93   4 -0.055510622  4 NA           1 1.423812  NA  NA  NA  NA  NA  NA     NA
      94   1 -0.421318463  4  3           1 1.423473  NA  NA  NA  NA  NA  NA     NA
      95   1  0.125295503  1  1           1 1.434412  NA  NA  NA  NA  NA  NA     NA
      96   3  0.213084904  4  3           1 1.450844  NA  NA  NA  NA  NA  NA     NA
      97   1 -0.161914659  4  2           1 1.433371  NA  NA  NA  NA  NA  NA     NA
      98   3 -0.034767685  3  2           1 1.444378  NA  NA  NA  NA  NA  NA     NA
      99   3 -0.320681689  3  4           1 1.422523  NA  NA  NA  NA  NA  NA     NA
      100  3  0.058192962  4  3           1 1.410394  NA  NA  NA  NA  NA  NA     NA
          M23:C2 M24:C2
      1       NA     NA
      2       NA     NA
      3       NA     NA
      4       NA     NA
      5       NA     NA
      6       NA     NA
      7       NA     NA
      8       NA     NA
      9       NA     NA
      10      NA     NA
      11      NA     NA
      12      NA     NA
      13      NA     NA
      14      NA     NA
      15      NA     NA
      16      NA     NA
      17      NA     NA
      18      NA     NA
      19      NA     NA
      20      NA     NA
      21      NA     NA
      22      NA     NA
      23      NA     NA
      24      NA     NA
      25      NA     NA
      26      NA     NA
      27      NA     NA
      28      NA     NA
      29      NA     NA
      30      NA     NA
      31      NA     NA
      32      NA     NA
      33      NA     NA
      34      NA     NA
      35      NA     NA
      36      NA     NA
      37      NA     NA
      38      NA     NA
      39      NA     NA
      40      NA     NA
      41      NA     NA
      42      NA     NA
      43      NA     NA
      44      NA     NA
      45      NA     NA
      46      NA     NA
      47      NA     NA
      48      NA     NA
      49      NA     NA
      50      NA     NA
      51      NA     NA
      52      NA     NA
      53      NA     NA
      54      NA     NA
      55      NA     NA
      56      NA     NA
      57      NA     NA
      58      NA     NA
      59      NA     NA
      60      NA     NA
      61      NA     NA
      62      NA     NA
      63      NA     NA
      64      NA     NA
      65      NA     NA
      66      NA     NA
      67      NA     NA
      68      NA     NA
      69      NA     NA
      70      NA     NA
      71      NA     NA
      72      NA     NA
      73      NA     NA
      74      NA     NA
      75      NA     NA
      76      NA     NA
      77      NA     NA
      78      NA     NA
      79      NA     NA
      80      NA     NA
      81      NA     NA
      82      NA     NA
      83      NA     NA
      84      NA     NA
      85      NA     NA
      86      NA     NA
      87      NA     NA
      88      NA     NA
      89      NA     NA
      90      NA     NA
      91      NA     NA
      92      NA     NA
      93      NA     NA
      94      NA     NA
      95      NA     NA
      96      NA     NA
      97      NA     NA
      98      NA     NA
      99      NA     NA
      100     NA     NA
      
      $m6e$spM_lvlone
                        center      scale
      O1                    NA         NA
      C2          -0.064905817 0.33317347
      M2                    NA         NA
      O2                    NA         NA
      (Intercept)           NA         NA
      C1           1.434100545 0.01299651
      M22                   NA         NA
      M23                   NA         NA
      M24                   NA         NA
      O22                   NA         NA
      O23                   NA         NA
      O24                   NA         NA
      M22:C2      -0.035803577 0.16299962
      M23:C2      -0.008443652 0.22326710
      M24:C2      -0.014114090 0.17029222
      
      $m6e$mu_reg_norm
      [1] 0
      
      $m6e$tau_reg_norm
      [1] 1e-04
      
      $m6e$shape_tau_norm
      [1] 0.01
      
      $m6e$rate_tau_norm
      [1] 0.01
      
      $m6e$mu_reg_multinomial
      [1] 0
      
      $m6e$tau_reg_multinomial
      [1] 1e-04
      
      $m6e$mu_reg_ordinal
      [1] 0
      
      $m6e$tau_reg_ordinal
      [1] 1e-04
      
      $m6e$mu_delta_ordinal
      [1] 0
      
      $m6e$tau_delta_ordinal
      [1] 1e-04
      
      

# jagsmodel remains the same

    Code
      lapply(models, "[[", "jagsmodel")
    Output
      $m0a
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- 0
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i]
        }
      
        # Priors for the model for O1
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2]) 
       }
      $m0b
      model { 
      
         # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- 0
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
        }
      
        # Priors for the model for O2
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       }
      $m1a
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- (M_lvlone[i, 3] - spM_lvlone[3, 1])/spM_lvlone[3, 2] * beta[1]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i]
        }
      
        # Priors for the model for O1
        for (k in 1:1) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2]) 
       }
      $m1b
      model { 
      
         # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 3] - spM_lvlone[3, 1])/spM_lvlone[3, 2] * beta[1]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
        }
      
        # Priors for the model for O2
        for (k in 1:1) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       }
      $m2a
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[1]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i]
        }
      
        # Priors for the model for O1
        for (k in 1:1) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 3] * alpha[1]
        }
      
        # Priors for the model for C2
        for (k in 1:1) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
       
       }
      $m2b
      model { 
      
         # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[1]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
        }
      
        # Priors for the model for O2
        for (k in 1:1) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 3] * alpha[1]
        }
      
        # Priors for the model for C2
        for (k in 1:1) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
       
       }
      $m3a
      model { 
      
         # Normal model for C1 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dnorm(mu_C1[i], tau_C1)
          mu_C1[i] <- M_lvlone[i, 2] * beta[1] + M_lvlone[i, 3] * beta[2] +
                      M_lvlone[i, 4] * beta[3] + M_lvlone[i, 5] * beta[4]
        }
      
        # Priors for the model for C1
        for (k in 1:4) {
          beta[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C1 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C1 <- sqrt(1/tau_C1)
       
       }
      $m3b
      model { 
      
         # Normal model for C1 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dnorm(mu_C1[i], tau_C1)
          mu_C1[i] <- M_lvlone[i, 3] * beta[1] + M_lvlone[i, 4] * beta[2] +
                      M_lvlone[i, 5] * beta[3] + M_lvlone[i, 6] * beta[4]
        }
      
        # Priors for the model for C1
        for (k in 1:4) {
          beta[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C1 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C1 <- sqrt(1/tau_C1)
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- 0
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 4] <- ifelse(M_lvlone[i, 2] == 2, 1, 0)
          M_lvlone[i, 5] <- ifelse(M_lvlone[i, 2] == 3, 1, 0)
          M_lvlone[i, 6] <- ifelse(M_lvlone[i, 2] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       }
      $m4a
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 6] * beta[1] + M_lvlone[i, 7] * beta[2] +
                       M_lvlone[i, 8] * beta[3] + M_lvlone[i, 9] * beta[4] +
                       M_lvlone[i, 10] * beta[5] + M_lvlone[i, 11] * beta[6] +
                       (M_lvlone[i, 12] - spM_lvlone[12, 1])/spM_lvlone[12, 2] * beta[7] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[8] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[9] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[10] +
                       (M_lvlone[i, 16] - spM_lvlone[16, 1])/spM_lvlone[16, 2] * beta[11]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i]
        }
      
        # Priors for the model for O1
        for (k in 1:11) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] + M_lvlone[i, 6] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] +
                      (M_lvlone[i, 17] - spM_lvlone[17, 1])/spM_lvlone[17, 2] * alpha[8]
      
          M_lvlone[i, 12] <- abs(M_lvlone[i, 17] - M_lvlone[i, 2])
      
      
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] + M_lvlone[i, 9] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               (M_lvlone[i, 17] - spM_lvlone[17, 1])/spM_lvlone[17, 2] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] + M_lvlone[i, 9] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               (M_lvlone[i, 17] - spM_lvlone[17, 1])/spM_lvlone[17, 2] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] + M_lvlone[i, 9] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               (M_lvlone[i, 17] - spM_lvlone[17, 1])/spM_lvlone[17, 2] * alpha[23]
      
          M_lvlone[i, 6] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 17] - spM_lvlone[17, 1])/spM_lvlone[17, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 14] <- M_lvlone[i, 9] * M_lvlone[i, 12]
          M_lvlone[i, 15] <- M_lvlone[i, 10] * M_lvlone[i, 12]
          M_lvlone[i, 16] <- M_lvlone[i, 11] * M_lvlone[i, 12]
        }
      
       }
      $m4b
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- (M_lvlone[i, 5] - spM_lvlone[5, 1])/spM_lvlone[5, 2] * beta[1] +
                       (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[2] +
                       (M_lvlone[i, 7] - spM_lvlone[7, 1])/spM_lvlone[7, 2] * beta[3] +
                       (M_lvlone[i, 8] - spM_lvlone[8, 1])/spM_lvlone[8, 2] * beta[4]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i]
        }
      
        # Priors for the model for O1
        for (k in 1:4) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 4] * alpha[1] + M_lvlone[i, 9] * alpha[2] +
                      M_lvlone[i, 10] * alpha[3] + M_lvlone[i, 11] * alpha[4] +
                      M_lvlone[i, 12] * alpha[5] + M_lvlone[i, 13] * alpha[6] +
                      M_lvlone[i, 14] * alpha[7] +
                      (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * alpha[8]
      
          M_lvlone[i, 6] <- abs(M_lvlone[i, 15] - M_lvlone[i, 2])
      
      
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- M_lvlone[i, 12] * alpha[9] + M_lvlone[i, 13] * alpha[10] +
                       M_lvlone[i, 14] * alpha[11] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * alpha[12]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
      
          M_lvlone[i, 5] <- ifelse((M_lvlone[i, 3]) > (M_lvlone[i, 16]), 1, 0)
      
        }
      
        # Priors for the model for O2
        for (k in 9:12) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 8] <- M_lvlone[i, 5] * M_lvlone[i, 6]
        }
      
       }
      $m5a
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 7] * beta[1] + M_lvlone[i, 8] * beta[2] +
                       M_lvlone[i, 9] * beta[3] + M_lvlone[i, 10] * beta[4] +
                       M_lvlone[i, 11] * beta[5] + M_lvlone[i, 12] * beta[6]
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[7] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[8]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[9] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[10]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[11] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[12]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:12) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       }
      $m5b
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 7] * beta[1] + M_lvlone[i, 8] * beta[2] +
                       M_lvlone[i, 9] * beta[3] + M_lvlone[i, 10] * beta[4] +
                       M_lvlone[i, 11] * beta[5] + M_lvlone[i, 12] * beta[6] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[7]
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[8] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[9]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[10] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[11]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[12] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[13]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:13) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 13] <- M_lvlone[i, 6] * M_lvlone[i, 2]
        }
      
       }
      $m5c
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 7] * beta[1] + M_lvlone[i, 8] * beta[2] +
                       M_lvlone[i, 9] * beta[3] + M_lvlone[i, 10] * beta[4] +
                       M_lvlone[i, 11] * beta[5] + M_lvlone[i, 12] * beta[6]
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[7] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[8] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[9]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[10] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[11] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[12]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[13] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[14] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[15]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:15) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 13] <- M_lvlone[i, 6] * M_lvlone[i, 2]
        }
      
       }
      $m5d
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 7] * beta[1] + M_lvlone[i, 8] * beta[2] +
                       M_lvlone[i, 9] * beta[3] + M_lvlone[i, 10] * beta[4] +
                       M_lvlone[i, 11] * beta[5] + M_lvlone[i, 12] * beta[6] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[7] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[8] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[9]
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[10] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[11]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[12] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[13]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[14] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[15]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:15) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 13] <- M_lvlone[i, 7] * M_lvlone[i, 2]
          M_lvlone[i, 14] <- M_lvlone[i, 8] * M_lvlone[i, 2]
          M_lvlone[i, 15] <- M_lvlone[i, 9] * M_lvlone[i, 2]
        }
      
       }
      $m5e
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- 0
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[1] +
                       M_lvlone[i, 7] * beta[2] + M_lvlone[i, 8] * beta[3] +
                       M_lvlone[i, 9] * beta[4] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[5] +
                       M_lvlone[i, 10] * beta[6] + M_lvlone[i, 11] * beta[7] +
                       M_lvlone[i, 12] * beta[8] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[9] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[10] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[11]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[12] +
                       M_lvlone[i, 7] * beta[13] + M_lvlone[i, 8] * beta[14] +
                       M_lvlone[i, 9] * beta[15] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[16] +
                       M_lvlone[i, 10] * beta[17] + M_lvlone[i, 11] * beta[18] +
                       M_lvlone[i, 12] * beta[19] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[20] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[21] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[22]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[23] +
                       M_lvlone[i, 7] * beta[24] + M_lvlone[i, 8] * beta[25] +
                       M_lvlone[i, 9] * beta[26] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[27] +
                       M_lvlone[i, 10] * beta[28] + M_lvlone[i, 11] * beta[29] +
                       M_lvlone[i, 12] * beta[30] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[31] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[32] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[33]
      
          p_O1[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 2:4])))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 1] - psum_O1[i, 2]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 3]))
          p_O1[i, 4] <- max(1e-10, min(1-1e-10, psum_O1[i, 3]))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:33) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] - exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] - exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 13] <- M_lvlone[i, 7] * M_lvlone[i, 2]
          M_lvlone[i, 14] <- M_lvlone[i, 8] * M_lvlone[i, 2]
          M_lvlone[i, 15] <- M_lvlone[i, 9] * M_lvlone[i, 2]
        }
      
       }
      $m6a
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 7] * beta[1] + M_lvlone[i, 8] * beta[2] +
                       M_lvlone[i, 9] * beta[3] + M_lvlone[i, 10] * beta[4] +
                       M_lvlone[i, 11] * beta[5] + M_lvlone[i, 12] * beta[6]
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[7] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[8]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[9] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[10]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[11] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[12]
      
          p_O1[i, 1] <- max(1e-10, min(1-1e-10, psum_O1[i, 1]))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 1]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 3] - psum_O1[i, 2]))
          p_O1[i, 4] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 1:3])))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:12) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] + exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] + exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       }
      $m6b
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 7] * beta[1] + M_lvlone[i, 8] * beta[2] +
                       M_lvlone[i, 9] * beta[3] + M_lvlone[i, 10] * beta[4] +
                       M_lvlone[i, 11] * beta[5] + M_lvlone[i, 12] * beta[6] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[7]
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[8] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[9]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[10] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[11]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[12] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[13]
      
          p_O1[i, 1] <- max(1e-10, min(1-1e-10, psum_O1[i, 1]))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 1]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 3] - psum_O1[i, 2]))
          p_O1[i, 4] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 1:3])))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:13) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] + exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] + exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 13] <- M_lvlone[i, 6] * M_lvlone[i, 2]
        }
      
       }
      $m6c
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 7] * beta[1] + M_lvlone[i, 8] * beta[2] +
                       M_lvlone[i, 9] * beta[3] + M_lvlone[i, 10] * beta[4] +
                       M_lvlone[i, 11] * beta[5] + M_lvlone[i, 12] * beta[6]
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[7] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[8] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[9]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[10] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[11] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[12]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[13] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[14] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[15]
      
          p_O1[i, 1] <- max(1e-10, min(1-1e-10, psum_O1[i, 1]))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 1]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 3] - psum_O1[i, 2]))
          p_O1[i, 4] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 1:3])))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:15) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] + exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] + exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 13] <- M_lvlone[i, 6] * M_lvlone[i, 2]
        }
      
       }
      $m6d
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- M_lvlone[i, 7] * beta[1] + M_lvlone[i, 8] * beta[2] +
                       M_lvlone[i, 9] * beta[3] + M_lvlone[i, 10] * beta[4] +
                       M_lvlone[i, 11] * beta[5] + M_lvlone[i, 12] * beta[6] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[7] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[8] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[9]
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[10] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[11]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[12] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[13]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[14] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[15]
      
          p_O1[i, 1] <- max(1e-10, min(1-1e-10, psum_O1[i, 1]))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 1]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 3] - psum_O1[i, 2]))
          p_O1[i, 4] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 1:3])))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:15) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] + exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] + exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 13] <- M_lvlone[i, 7] * M_lvlone[i, 2]
          M_lvlone[i, 14] <- M_lvlone[i, 8] * M_lvlone[i, 2]
          M_lvlone[i, 15] <- M_lvlone[i, 9] * M_lvlone[i, 2]
        }
      
       }
      $m6e
      model { 
      
         # Cumulative logit model for O1 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 1] ~ dcat(p_O1[i, 1:4])
          eta_O1[i] <- 0
      
          eta_O1_1[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[1] +
                       M_lvlone[i, 7] * beta[2] + M_lvlone[i, 8] * beta[3] +
                       M_lvlone[i, 9] * beta[4] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[5] +
                       M_lvlone[i, 10] * beta[6] + M_lvlone[i, 11] * beta[7] +
                       M_lvlone[i, 12] * beta[8] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[9] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[10] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[11]
          eta_O1_2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[12] +
                       M_lvlone[i, 7] * beta[13] + M_lvlone[i, 8] * beta[14] +
                       M_lvlone[i, 9] * beta[15] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[16] +
                       M_lvlone[i, 10] * beta[17] + M_lvlone[i, 11] * beta[18] +
                       M_lvlone[i, 12] * beta[19] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[20] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[21] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[22]
          eta_O1_3[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * beta[23] +
                       M_lvlone[i, 7] * beta[24] + M_lvlone[i, 8] * beta[25] +
                       M_lvlone[i, 9] * beta[26] +
                       (M_lvlone[i, 2] - spM_lvlone[2, 1])/spM_lvlone[2, 2] * beta[27] +
                       M_lvlone[i, 10] * beta[28] + M_lvlone[i, 11] * beta[29] +
                       M_lvlone[i, 12] * beta[30] +
                       (M_lvlone[i, 13] - spM_lvlone[13, 1])/spM_lvlone[13, 2] * beta[31] +
                       (M_lvlone[i, 14] - spM_lvlone[14, 1])/spM_lvlone[14, 2] * beta[32] +
                       (M_lvlone[i, 15] - spM_lvlone[15, 1])/spM_lvlone[15, 2] * beta[33]
      
          p_O1[i, 1] <- max(1e-10, min(1-1e-10, psum_O1[i, 1]))
          p_O1[i, 2] <- max(1e-10, min(1-1e-10, psum_O1[i, 2] - psum_O1[i, 1]))
          p_O1[i, 3] <- max(1e-10, min(1-1e-10, psum_O1[i, 3] - psum_O1[i, 2]))
          p_O1[i, 4] <- 1 - max(1e-10, min(1-1e-10, sum(p_O1[i, 1:3])))
      
          logit(psum_O1[i, 1]) <- gamma_O1[1] + eta_O1[i] + eta_O1_1[i]
          logit(psum_O1[i, 2]) <- gamma_O1[2] + eta_O1[i] + eta_O1_2[i]
          logit(psum_O1[i, 3]) <- gamma_O1[3] + eta_O1[i] + eta_O1_3[i]
        }
      
        # Priors for the model for O1
        for (k in 1:33) {
          beta[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O1[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O1[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O1[2] <- gamma_O1[1] + exp(delta_O1[1])
        gamma_O1[3] <- gamma_O1[2] + exp(delta_O1[2])
      
      
        # Normal model for C2 -----------------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 2] ~ dnorm(mu_C2[i], tau_C2)
          mu_C2[i] <- M_lvlone[i, 5] * alpha[1] +
                      (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[2] +
                      M_lvlone[i, 7] * alpha[3] + M_lvlone[i, 8] * alpha[4] +
                      M_lvlone[i, 9] * alpha[5] + M_lvlone[i, 10] * alpha[6] +
                      M_lvlone[i, 11] * alpha[7] + M_lvlone[i, 12] * alpha[8]
        }
      
        # Priors for the model for C2
        for (k in 1:8) {
          alpha[k] ~ dnorm(mu_reg_norm, tau_reg_norm)
        }
        tau_C2 ~ dgamma(shape_tau_norm, rate_tau_norm)
        sigma_C2 <- sqrt(1/tau_C2)
      
      
      
        # Multinomial logit model for M2 ------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 3] ~ dcat(p_M2[i, 1:4])
      
          p_M2[i, 1] <- min(1-1e-7, max(1e-7, phi_M2[i, 1] / sum(phi_M2[i, ])))
          p_M2[i, 2] <- min(1-1e-7, max(1e-7, phi_M2[i, 2] / sum(phi_M2[i, ])))
          p_M2[i, 3] <- min(1-1e-7, max(1e-7, phi_M2[i, 3] / sum(phi_M2[i, ])))
          p_M2[i, 4] <- min(1-1e-7, max(1e-7, phi_M2[i, 4] / sum(phi_M2[i, ])))
      
          log(phi_M2[i, 1]) <- 0
          log(phi_M2[i, 2]) <- M_lvlone[i, 5] * alpha[9] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[10] +
                               M_lvlone[i, 10] * alpha[11] + M_lvlone[i, 11] * alpha[12] +
                               M_lvlone[i, 12] * alpha[13]
          log(phi_M2[i, 3]) <- M_lvlone[i, 5] * alpha[14] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[15] +
                               M_lvlone[i, 10] * alpha[16] + M_lvlone[i, 11] * alpha[17] +
                               M_lvlone[i, 12] * alpha[18]
          log(phi_M2[i, 4]) <- M_lvlone[i, 5] * alpha[19] +
                               (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[20] +
                               M_lvlone[i, 10] * alpha[21] + M_lvlone[i, 11] * alpha[22] +
                               M_lvlone[i, 12] * alpha[23]
      
          M_lvlone[i, 7] <- ifelse(M_lvlone[i, 3] == 2, 1, 0)
          M_lvlone[i, 8] <- ifelse(M_lvlone[i, 3] == 3, 1, 0)
          M_lvlone[i, 9] <- ifelse(M_lvlone[i, 3] == 4, 1, 0)
      
        }
      
        # Priors for the model for M2
        for (k in 9:23) {
          alpha[k] ~ dnorm(mu_reg_multinomial, tau_reg_multinomial)
        }
      
      
      
        # Cumulative logit model for O2 -------------------------------------------------
        for (i in 1:100) {
          M_lvlone[i, 4] ~ dcat(p_O2[i, 1:4])
          eta_O2[i] <- (M_lvlone[i, 6] - spM_lvlone[6, 1])/spM_lvlone[6, 2] * alpha[24]
      
          p_O2[i, 1] <- 1 - max(1e-10, min(1-1e-10, sum(p_O2[i, 2:4])))
          p_O2[i, 2] <- max(1e-10, min(1-1e-10, psum_O2[i, 1] - psum_O2[i, 2]))
          p_O2[i, 3] <- max(1e-10, min(1-1e-10, psum_O2[i, 2] - psum_O2[i, 3]))
          p_O2[i, 4] <- max(1e-10, min(1-1e-10, psum_O2[i, 3]))
      
          logit(psum_O2[i, 1]) <- gamma_O2[1] + eta_O2[i]
          logit(psum_O2[i, 2]) <- gamma_O2[2] + eta_O2[i]
          logit(psum_O2[i, 3]) <- gamma_O2[3] + eta_O2[i]
      
          M_lvlone[i, 10] <- ifelse(M_lvlone[i, 4] == 2, 1, 0)
          M_lvlone[i, 11] <- ifelse(M_lvlone[i, 4] == 3, 1, 0)
          M_lvlone[i, 12] <- ifelse(M_lvlone[i, 4] == 4, 1, 0)
        }
      
        # Priors for the model for O2
        for (k in 24:24) {
          alpha[k] ~ dnorm(mu_reg_ordinal, tau_reg_ordinal)
        }
      
        delta_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        delta_O2[2] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
      
        gamma_O2[1] ~ dnorm(mu_delta_ordinal, tau_delta_ordinal)
        gamma_O2[2] <- gamma_O2[1] - exp(delta_O2[1])
        gamma_O2[3] <- gamma_O2[2] - exp(delta_O2[2]) 
       
        # Re-calculate interaction terms
        for (i in 1:100) {
          M_lvlone[i, 13] <- M_lvlone[i, 7] * M_lvlone[i, 2]
          M_lvlone[i, 14] <- M_lvlone[i, 8] * M_lvlone[i, 2]
          M_lvlone[i, 15] <- M_lvlone[i, 9] * M_lvlone[i, 2]
        }
      
       }

# GRcrit and MCerror give same result

    Code
      lapply(models0, GR_crit, multivariate = FALSE)
    Output
      $m0a
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m0b
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      gamma_O2[1]        NaN        NaN
      gamma_O2[2]        NaN        NaN
      gamma_O2[3]        NaN        NaN
      
      
      $m1a
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      C1                 NaN        NaN
      
      
      $m1b
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      gamma_O2[1]        NaN        NaN
      gamma_O2[2]        NaN        NaN
      gamma_O2[3]        NaN        NaN
      C1                 NaN        NaN
      
      
      $m2a
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      C2                 NaN        NaN
      
      
      $m2b
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      gamma_O2[1]        NaN        NaN
      gamma_O2[2]        NaN        NaN
      gamma_O2[3]        NaN        NaN
      C2                 NaN        NaN
      
      
      $m3a
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      (Intercept)        NaN        NaN
      O1.L               NaN        NaN
      O1.Q               NaN        NaN
      O1.C               NaN        NaN
      sigma_C1           NaN        NaN
      
      
      $m3b
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      (Intercept)        NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      sigma_C1           NaN        NaN
      
      
      $m4a
      Potential scale reduction factors:
      
                       Point est. Upper C.I.
      M22                     NaN        NaN
      M23                     NaN        NaN
      M24                     NaN        NaN
      O22                     NaN        NaN
      O23                     NaN        NaN
      O24                     NaN        NaN
      abs(C1 - C2)            NaN        NaN
      log(C1)                 NaN        NaN
      O22:abs(C1 - C2)        NaN        NaN
      O23:abs(C1 - C2)        NaN        NaN
      O24:abs(C1 - C2)        NaN        NaN
      gamma_O1[1]             NaN        NaN
      gamma_O1[2]             NaN        NaN
      gamma_O1[3]             NaN        NaN
      
      
      $m4b
      Potential scale reduction factors:
      
                                                                 Point est.
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                     NaN
      abs(C1 - C2)                                                      NaN
      log(C1)                                                           NaN
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)        NaN
      gamma_O1[1]                                                       NaN
      gamma_O1[2]                                                       NaN
      gamma_O1[3]                                                       NaN
                                                                 Upper C.I.
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                     NaN
      abs(C1 - C2)                                                      NaN
      log(C1)                                                           NaN
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)        NaN
      gamma_O1[1]                                                       NaN
      gamma_O1[2]                                                       NaN
      gamma_O1[3]                                                       NaN
      
      
      $m5a
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      M22                NaN        NaN
      M23                NaN        NaN
      M24                NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      O12: C1            NaN        NaN
      O12: C2            NaN        NaN
      O13: C1            NaN        NaN
      O13: C2            NaN        NaN
      O14: C1            NaN        NaN
      O14: C2            NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m5b
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      M22                NaN        NaN
      M23                NaN        NaN
      M24                NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      C1:C2              NaN        NaN
      O12: C1            NaN        NaN
      O12: C2            NaN        NaN
      O13: C1            NaN        NaN
      O13: C2            NaN        NaN
      O14: C1            NaN        NaN
      O14: C2            NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m5c
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      M22                NaN        NaN
      M23                NaN        NaN
      M24                NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      O12: C1            NaN        NaN
      O12: C2            NaN        NaN
      O12: C1:C2         NaN        NaN
      O13: C1            NaN        NaN
      O13: C2            NaN        NaN
      O13: C1:C2         NaN        NaN
      O14: C1            NaN        NaN
      O14: C2            NaN        NaN
      O14: C1:C2         NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m5d
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      M22                NaN        NaN
      M23                NaN        NaN
      M24                NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      M22:C2             NaN        NaN
      M23:C2             NaN        NaN
      M24:C2             NaN        NaN
      O12: C1            NaN        NaN
      O12: C2            NaN        NaN
      O13: C1            NaN        NaN
      O13: C2            NaN        NaN
      O14: C1            NaN        NaN
      O14: C2            NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m5e
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      O12: C1            NaN        NaN
      O12: M22           NaN        NaN
      O12: M23           NaN        NaN
      O12: M24           NaN        NaN
      O12: C2            NaN        NaN
      O12: O22           NaN        NaN
      O12: O23           NaN        NaN
      O12: O24           NaN        NaN
      O12: M22:C2        NaN        NaN
      O12: M23:C2        NaN        NaN
      O12: M24:C2        NaN        NaN
      O13: C1            NaN        NaN
      O13: M22           NaN        NaN
      O13: M23           NaN        NaN
      O13: M24           NaN        NaN
      O13: C2            NaN        NaN
      O13: O22           NaN        NaN
      O13: O23           NaN        NaN
      O13: O24           NaN        NaN
      O13: M22:C2        NaN        NaN
      O13: M23:C2        NaN        NaN
      O13: M24:C2        NaN        NaN
      O14: C1            NaN        NaN
      O14: M22           NaN        NaN
      O14: M23           NaN        NaN
      O14: M24           NaN        NaN
      O14: C2            NaN        NaN
      O14: O22           NaN        NaN
      O14: O23           NaN        NaN
      O14: O24           NaN        NaN
      O14: M22:C2        NaN        NaN
      O14: M23:C2        NaN        NaN
      O14: M24:C2        NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m6a
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      M22                NaN        NaN
      M23                NaN        NaN
      M24                NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      O12: C1            NaN        NaN
      O12: C2            NaN        NaN
      O13: C1            NaN        NaN
      O13: C2            NaN        NaN
      O14: C1            NaN        NaN
      O14: C2            NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m6b
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      M22                NaN        NaN
      M23                NaN        NaN
      M24                NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      C1:C2              NaN        NaN
      O12: C1            NaN        NaN
      O12: C2            NaN        NaN
      O13: C1            NaN        NaN
      O13: C2            NaN        NaN
      O14: C1            NaN        NaN
      O14: C2            NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m6c
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      M22                NaN        NaN
      M23                NaN        NaN
      M24                NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      O12: C1            NaN        NaN
      O12: C2            NaN        NaN
      O12: C1:C2         NaN        NaN
      O13: C1            NaN        NaN
      O13: C2            NaN        NaN
      O13: C1:C2         NaN        NaN
      O14: C1            NaN        NaN
      O14: C2            NaN        NaN
      O14: C1:C2         NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m6d
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      M22                NaN        NaN
      M23                NaN        NaN
      M24                NaN        NaN
      O22                NaN        NaN
      O23                NaN        NaN
      O24                NaN        NaN
      M22:C2             NaN        NaN
      M23:C2             NaN        NaN
      M24:C2             NaN        NaN
      O12: C1            NaN        NaN
      O12: C2            NaN        NaN
      O13: C1            NaN        NaN
      O13: C2            NaN        NaN
      O14: C1            NaN        NaN
      O14: C2            NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      
      $m6e
      Potential scale reduction factors:
      
                  Point est. Upper C.I.
      O12: C1            NaN        NaN
      O12: M22           NaN        NaN
      O12: M23           NaN        NaN
      O12: M24           NaN        NaN
      O12: C2            NaN        NaN
      O12: O22           NaN        NaN
      O12: O23           NaN        NaN
      O12: O24           NaN        NaN
      O12: M22:C2        NaN        NaN
      O12: M23:C2        NaN        NaN
      O12: M24:C2        NaN        NaN
      O13: C1            NaN        NaN
      O13: M22           NaN        NaN
      O13: M23           NaN        NaN
      O13: M24           NaN        NaN
      O13: C2            NaN        NaN
      O13: O22           NaN        NaN
      O13: O23           NaN        NaN
      O13: O24           NaN        NaN
      O13: M22:C2        NaN        NaN
      O13: M23:C2        NaN        NaN
      O13: M24:C2        NaN        NaN
      O14: C1            NaN        NaN
      O14: M22           NaN        NaN
      O14: M23           NaN        NaN
      O14: M24           NaN        NaN
      O14: C2            NaN        NaN
      O14: O22           NaN        NaN
      O14: O23           NaN        NaN
      O14: O24           NaN        NaN
      O14: M22:C2        NaN        NaN
      O14: M23:C2        NaN        NaN
      O14: M24:C2        NaN        NaN
      gamma_O1[1]        NaN        NaN
      gamma_O1[2]        NaN        NaN
      gamma_O1[3]        NaN        NaN
      
      

---

    Code
      lapply(models0, MC_error)
    Output
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      $m0a
                  est MCSE SD MCSE/SD
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m0b
                  est MCSE SD MCSE/SD
      gamma_O2[1]   0    0  0     NaN
      gamma_O2[2]   0    0  0     NaN
      gamma_O2[3]   0    0  0     NaN
      
      $m1a
                  est MCSE SD MCSE/SD
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      C1            0    0  0     NaN
      
      $m1b
                  est MCSE SD MCSE/SD
      gamma_O2[1]   0    0  0     NaN
      gamma_O2[2]   0    0  0     NaN
      gamma_O2[3]   0    0  0     NaN
      C1            0    0  0     NaN
      
      $m2a
                  est MCSE SD MCSE/SD
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      C2            0    0  0     NaN
      
      $m2b
                  est MCSE SD MCSE/SD
      gamma_O2[1]   0    0  0     NaN
      gamma_O2[2]   0    0  0     NaN
      gamma_O2[3]   0    0  0     NaN
      C2            0    0  0     NaN
      
      $m3a
                  est MCSE SD MCSE/SD
      (Intercept)   0    0  0     NaN
      O1.L          0    0  0     NaN
      O1.Q          0    0  0     NaN
      O1.C          0    0  0     NaN
      sigma_C1      0    0  0     NaN
      
      $m3b
                  est MCSE SD MCSE/SD
      (Intercept)   0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      sigma_C1      0    0  0     NaN
      
      $m4a
                       est MCSE SD MCSE/SD
      M22                0    0  0     NaN
      M23                0    0  0     NaN
      M24                0    0  0     NaN
      O22                0    0  0     NaN
      O23                0    0  0     NaN
      O24                0    0  0     NaN
      abs(C1 - C2)       0    0  0     NaN
      log(C1)            0    0  0     NaN
      O22:abs(C1 - C2)   0    0  0     NaN
      O23:abs(C1 - C2)   0    0  0     NaN
      O24:abs(C1 - C2)   0    0  0     NaN
      gamma_O1[1]        0    0  0     NaN
      gamma_O1[2]        0    0  0     NaN
      gamma_O1[3]        0    0  0     NaN
      
      $m4b
                                                                 est MCSE SD MCSE/SD
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                0    0  0     NaN
      abs(C1 - C2)                                                 0    0  0     NaN
      log(C1)                                                      0    0  0     NaN
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)   0    0  0     NaN
      gamma_O1[1]                                                  0    0  0     NaN
      gamma_O1[2]                                                  0    0  0     NaN
      gamma_O1[3]                                                  0    0  0     NaN
      
      $m5a
                  est MCSE SD MCSE/SD
      M22           0    0  0     NaN
      M23           0    0  0     NaN
      M24           0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      O12: C1       0    0  0     NaN
      O12: C2       0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: C2       0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: C2       0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m5b
                  est MCSE SD MCSE/SD
      M22           0    0  0     NaN
      M23           0    0  0     NaN
      M24           0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      C1:C2         0    0  0     NaN
      O12: C1       0    0  0     NaN
      O12: C2       0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: C2       0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: C2       0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m5c
                  est MCSE SD MCSE/SD
      M22           0    0  0     NaN
      M23           0    0  0     NaN
      M24           0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      O12: C1       0    0  0     NaN
      O12: C2       0    0  0     NaN
      O12: C1:C2    0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: C2       0    0  0     NaN
      O13: C1:C2    0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: C2       0    0  0     NaN
      O14: C1:C2    0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m5d
                  est MCSE SD MCSE/SD
      M22           0    0  0     NaN
      M23           0    0  0     NaN
      M24           0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      M22:C2        0    0  0     NaN
      M23:C2        0    0  0     NaN
      M24:C2        0    0  0     NaN
      O12: C1       0    0  0     NaN
      O12: C2       0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: C2       0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: C2       0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m5e
                  est MCSE SD MCSE/SD
      O12: C1       0    0  0     NaN
      O12: M22      0    0  0     NaN
      O12: M23      0    0  0     NaN
      O12: M24      0    0  0     NaN
      O12: C2       0    0  0     NaN
      O12: O22      0    0  0     NaN
      O12: O23      0    0  0     NaN
      O12: O24      0    0  0     NaN
      O12: M22:C2   0    0  0     NaN
      O12: M23:C2   0    0  0     NaN
      O12: M24:C2   0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: M22      0    0  0     NaN
      O13: M23      0    0  0     NaN
      O13: M24      0    0  0     NaN
      O13: C2       0    0  0     NaN
      O13: O22      0    0  0     NaN
      O13: O23      0    0  0     NaN
      O13: O24      0    0  0     NaN
      O13: M22:C2   0    0  0     NaN
      O13: M23:C2   0    0  0     NaN
      O13: M24:C2   0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: M22      0    0  0     NaN
      O14: M23      0    0  0     NaN
      O14: M24      0    0  0     NaN
      O14: C2       0    0  0     NaN
      O14: O22      0    0  0     NaN
      O14: O23      0    0  0     NaN
      O14: O24      0    0  0     NaN
      O14: M22:C2   0    0  0     NaN
      O14: M23:C2   0    0  0     NaN
      O14: M24:C2   0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m6a
                  est MCSE SD MCSE/SD
      M22           0    0  0     NaN
      M23           0    0  0     NaN
      M24           0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      O12: C1       0    0  0     NaN
      O12: C2       0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: C2       0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: C2       0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m6b
                  est MCSE SD MCSE/SD
      M22           0    0  0     NaN
      M23           0    0  0     NaN
      M24           0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      C1:C2         0    0  0     NaN
      O12: C1       0    0  0     NaN
      O12: C2       0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: C2       0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: C2       0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m6c
                  est MCSE SD MCSE/SD
      M22           0    0  0     NaN
      M23           0    0  0     NaN
      M24           0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      O12: C1       0    0  0     NaN
      O12: C2       0    0  0     NaN
      O12: C1:C2    0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: C2       0    0  0     NaN
      O13: C1:C2    0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: C2       0    0  0     NaN
      O14: C1:C2    0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m6d
                  est MCSE SD MCSE/SD
      M22           0    0  0     NaN
      M23           0    0  0     NaN
      M24           0    0  0     NaN
      O22           0    0  0     NaN
      O23           0    0  0     NaN
      O24           0    0  0     NaN
      M22:C2        0    0  0     NaN
      M23:C2        0    0  0     NaN
      M24:C2        0    0  0     NaN
      O12: C1       0    0  0     NaN
      O12: C2       0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: C2       0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: C2       0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      
      $m6e
                  est MCSE SD MCSE/SD
      O12: C1       0    0  0     NaN
      O12: M22      0    0  0     NaN
      O12: M23      0    0  0     NaN
      O12: M24      0    0  0     NaN
      O12: C2       0    0  0     NaN
      O12: O22      0    0  0     NaN
      O12: O23      0    0  0     NaN
      O12: O24      0    0  0     NaN
      O12: M22:C2   0    0  0     NaN
      O12: M23:C2   0    0  0     NaN
      O12: M24:C2   0    0  0     NaN
      O13: C1       0    0  0     NaN
      O13: M22      0    0  0     NaN
      O13: M23      0    0  0     NaN
      O13: M24      0    0  0     NaN
      O13: C2       0    0  0     NaN
      O13: O22      0    0  0     NaN
      O13: O23      0    0  0     NaN
      O13: O24      0    0  0     NaN
      O13: M22:C2   0    0  0     NaN
      O13: M23:C2   0    0  0     NaN
      O13: M24:C2   0    0  0     NaN
      O14: C1       0    0  0     NaN
      O14: M22      0    0  0     NaN
      O14: M23      0    0  0     NaN
      O14: M24      0    0  0     NaN
      O14: C2       0    0  0     NaN
      O14: O22      0    0  0     NaN
      O14: O23      0    0  0     NaN
      O14: O24      0    0  0     NaN
      O14: M22:C2   0    0  0     NaN
      O14: M23:C2   0    0  0     NaN
      O14: M24:C2   0    0  0     NaN
      gamma_O1[1]   0    0  0     NaN
      gamma_O1[2]   0    0  0     NaN
      gamma_O1[3]   0    0  0     NaN
      

# summary output remained the same on Windows

    Code
      lapply(models0, print)
    Output
      
      Call:
      clm_imp(formula = O1 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3 
           0      0      0 
      
      Call:
      clm_imp(formula = O2 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O2" 
      
      
      Coefficients:
      O2 > 1 O2 > 2 O2 > 3 
           0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3     C1 
           0      0      0      0 
      
      Call:
      clm_imp(formula = O2 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O2" 
      
      
      Coefficients:
      O2 > 1 O2 > 2 O2 > 3     C1 
           0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3     C2 
           0      0      0      0 
      
      Call:
      clm_imp(formula = O2 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O2" 
      
      
      Coefficients:
      O2 > 1 O2 > 2 O2 > 3     C2 
           0      0      0      0 
      
      Call:
      lm_imp(formula = C1 ~ O1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian linear model for "C1" 
      
      
      Coefficients:
      (Intercept)        O1.L        O1.Q        O1.C 
                0           0           0           0 
      
      
      Residual standard deviation:
      sigma_C1 
             0 
      
      Call:
      lm_imp(formula = C1 ~ O2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian linear model for "C1" 
      
      
      Coefficients:
      (Intercept)         O22         O23         O24 
                0           0           0           0 
      
      
      Residual standard deviation:
      sigma_C1 
             0 
      
      Call:
      clm_imp(formula = O1 ~ M2 + O2 * abs(C1 - C2) + log(C1), data = wideDF, 
          n.adapt = 5, n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
                O1 > 1           O1 > 2           O1 > 3              M22 
                     0                0                0                0 
                   M23              M24              O22              O23 
                     0                0                0                0 
                   O24     abs(C1 - C2)          log(C1) O22:abs(C1 - C2) 
                     0                0                0                0 
      O23:abs(C1 - C2) O24:abs(C1 - C2) 
                     0                0 
      
      Call:
      clm_imp(formula = O1 ~ ifelse(as.numeric(O2) > as.numeric(M1), 
          1, 0) * abs(C1 - C2) + log(C1), data = wideDF, n.adapt = 5, 
          n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
                                                          O1 > 1 
                                                               0 
                                                          O1 > 2 
                                                               0 
                                                          O1 > 3 
                                                               0 
                   ifelse(as.numeric(O2) > as.numeric(M1), 1, 0) 
                                                               0 
                                                    abs(C1 - C2) 
                                                               0 
                                                         log(C1) 
                                                               0 
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2) 
                                                               0 
      
      Call:
      clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1     C2     C1     C2 
           0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24  C1:C2     C1 
           0      0      0      0      0      0      0      0      0      0      0 
          C2     C1     C2     C1     C2 
           0      0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
       C1:C2     C1     C2  C1:C2     C1     C2  C1:C2 
           0      0      0      0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 
           0      0      0      0      0      0      0      0      0      0      0 
      M24:C2     C1     C2     C1     C2     C1     C2 
           0      0      0      0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
              M2 * C2 + O2, seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2 
           0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3    M22    M23    M24    O22    O23    O24     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1     C2     C1     C2 
           0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3    M22    M23    M24    O22    O23    O24  C1:C2     C1 
           0      0      0      0      0      0      0      0      0      0      0 
          C2     C1     C2     C1     C2 
           0      0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3    M22    M23    M24    O22    O23    O24     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
       C1:C2     C1     C2  C1:C2     C1     C2  C1:C2 
           0      0      0      0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3    M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 
           0      0      0      0      0      0      0      0      0      0      0 
      M24:C2     C1     C2     C1     C2     C1     C2 
           0      0      0      0      0      0      0 
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
              M2 * C2 + O2, rev = "O1", seed = 2020, warn = FALSE, 
          mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2 
           0      0      0 
      $m0a
      
      Call:
      clm_imp(formula = O1 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3 
           0      0      0 
      
      $m0b
      
      Call:
      clm_imp(formula = O2 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O2" 
      
      
      Coefficients:
      O2 > 1 O2 > 2 O2 > 3 
           0      0      0 
      
      $m1a
      
      Call:
      clm_imp(formula = O1 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3     C1 
           0      0      0      0 
      
      $m1b
      
      Call:
      clm_imp(formula = O2 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O2" 
      
      
      Coefficients:
      O2 > 1 O2 > 2 O2 > 3     C1 
           0      0      0      0 
      
      $m2a
      
      Call:
      clm_imp(formula = O1 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3     C2 
           0      0      0      0 
      
      $m2b
      
      Call:
      clm_imp(formula = O2 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O2" 
      
      
      Coefficients:
      O2 > 1 O2 > 2 O2 > 3     C2 
           0      0      0      0 
      
      $m3a
      
      Call:
      lm_imp(formula = C1 ~ O1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian linear model for "C1" 
      
      
      Coefficients:
      (Intercept)        O1.L        O1.Q        O1.C 
                0           0           0           0 
      
      
      Residual standard deviation:
      sigma_C1 
             0 
      
      $m3b
      
      Call:
      lm_imp(formula = C1 ~ O2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian linear model for "C1" 
      
      
      Coefficients:
      (Intercept)         O22         O23         O24 
                0           0           0           0 
      
      
      Residual standard deviation:
      sigma_C1 
             0 
      
      $m4a
      
      Call:
      clm_imp(formula = O1 ~ M2 + O2 * abs(C1 - C2) + log(C1), data = wideDF, 
          n.adapt = 5, n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
                O1 > 1           O1 > 2           O1 > 3              M22 
                     0                0                0                0 
                   M23              M24              O22              O23 
                     0                0                0                0 
                   O24     abs(C1 - C2)          log(C1) O22:abs(C1 - C2) 
                     0                0                0                0 
      O23:abs(C1 - C2) O24:abs(C1 - C2) 
                     0                0 
      
      $m4b
      
      Call:
      clm_imp(formula = O1 ~ ifelse(as.numeric(O2) > as.numeric(M1), 
          1, 0) * abs(C1 - C2) + log(C1), data = wideDF, n.adapt = 5, 
          n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
                                                          O1 > 1 
                                                               0 
                                                          O1 > 2 
                                                               0 
                                                          O1 > 3 
                                                               0 
                   ifelse(as.numeric(O2) > as.numeric(M1), 1, 0) 
                                                               0 
                                                    abs(C1 - C2) 
                                                               0 
                                                         log(C1) 
                                                               0 
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2) 
                                                               0 
      
      $m5a
      
      Call:
      clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1     C2     C1     C2 
           0      0      0      0 
      
      $m5b
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24  C1:C2     C1 
           0      0      0      0      0      0      0      0      0      0      0 
          C2     C1     C2     C1     C2 
           0      0      0      0      0 
      
      $m5c
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
       C1:C2     C1     C2  C1:C2     C1     C2  C1:C2 
           0      0      0      0      0      0      0 
      
      $m5d
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 
           0      0      0      0      0      0      0      0      0      0      0 
      M24:C2     C1     C2     C1     C2     C1     C2 
           0      0      0      0      0      0      0 
      
      $m5e
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
              M2 * C2 + O2, seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 > 1 O1 > 2 O1 > 3     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2 
           0      0      0 
      
      $m6a
      
      Call:
      clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3    M22    M23    M24    O22    O23    O24     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1     C2     C1     C2 
           0      0      0      0 
      
      $m6b
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3    M22    M23    M24    O22    O23    O24  C1:C2     C1 
           0      0      0      0      0      0      0      0      0      0      0 
          C2     C1     C2     C1     C2 
           0      0      0      0      0 
      
      $m6c
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3    M22    M23    M24    O22    O23    O24     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
       C1:C2     C1     C2  C1:C2     C1     C2  C1:C2 
           0      0      0      0      0      0      0 
      
      $m6d
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3    M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 
           0      0      0      0      0      0      0      0      0      0      0 
      M24:C2     C1     C2     C1     C2     C1     C2 
           0      0      0      0      0      0      0 
      
      $m6e
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
              M2 * C2 + O2, rev = "O1", seed = 2020, warn = FALSE, 
          mess = FALSE)
      
       Bayesian cumulative logit model for "O1" 
      
      
      Coefficients:
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
           0      0      0      0      0      0      0      0      0      0      0 
      M22:C2 M23:C2 M24:C2 
           0      0      0 
      

---

    Code
      lapply(models0, coef)
    Output
      $m0a
      $m0a$O1
      O1 > 1 O1 > 2 O1 > 3 
           0      0      0 
      
      
      $m0b
      $m0b$O2
      O2 > 1 O2 > 2 O2 > 3 
           0      0      0 
      
      
      $m1a
      $m1a$O1
          C1 O1 > 1 O1 > 2 O1 > 3 
           0      0      0      0 
      
      
      $m1b
      $m1b$O2
          C1 O2 > 1 O2 > 2 O2 > 3 
           0      0      0      0 
      
      
      $m2a
      $m2a$O1
          C2 O1 > 1 O1 > 2 O1 > 3 
           0      0      0      0 
      
      
      $m2b
      $m2b$O2
          C2 O2 > 1 O2 > 2 O2 > 3 
           0      0      0      0 
      
      
      $m3a
      $m3a$C1
      (Intercept)        O1.L        O1.Q        O1.C    sigma_C1 
                0           0           0           0           0 
      
      
      $m3b
      $m3b$C1
      (Intercept)         O22         O23         O24    sigma_C1 
                0           0           0           0           0 
      
      
      $m4a
      $m4a$O1
                   M22              M23              M24              O22 
                     0                0                0                0 
                   O23              O24     abs(C1 - C2)          log(C1) 
                     0                0                0                0 
      O22:abs(C1 - C2) O23:abs(C1 - C2) O24:abs(C1 - C2)           O1 > 1 
                     0                0                0                0 
                O1 > 2           O1 > 3 
                     0                0 
      
      
      $m4b
      $m4b$O1
                   ifelse(as.numeric(O2) > as.numeric(M1), 1, 0) 
                                                               0 
                                                    abs(C1 - C2) 
                                                               0 
                                                         log(C1) 
                                                               0 
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2) 
                                                               0 
                                                          O1 > 1 
                                                               0 
                                                          O1 > 2 
                                                               0 
                                                          O1 > 3 
                                                               0 
      
      
      $m5a
      $m5a$O1
         M22    M23    M24    O22    O23    O24     C1     C2     C1     C2     C1 
           0      0      0      0      0      0      0      0      0      0      0 
          C2 O1 > 1 O1 > 2 O1 > 3 
           0      0      0      0 
      
      
      $m5b
      $m5b$O1
         M22    M23    M24    O22    O23    O24  C1:C2     C1     C2     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1     C2 O1 > 1 O1 > 2 O1 > 3 
           0      0      0      0      0 
      
      
      $m5c
      $m5c$O1
         M22    M23    M24    O22    O23    O24     C1     C2  C1:C2     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
       C1:C2     C1     C2  C1:C2 O1 > 1 O1 > 2 O1 > 3 
           0      0      0      0      0      0      0 
      
      
      $m5d
      $m5d$O1
         M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 M24:C2     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1     C2     C1     C2 O1 > 1 O1 > 2 O1 > 3 
           0      0      0      0      0      0      0 
      
      
      $m5e
      $m5e$O1
          C1    M22    M23    M24     C2    O22    O23    O24 M22:C2 M23:C2 M24:C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1    M22    M23    M24     C2    O22    O23    O24 M22:C2 M23:C2 M24:C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1    M22    M23    M24     C2    O22    O23    O24 M22:C2 M23:C2 M24:C2 
           0      0      0      0      0      0      0      0      0      0      0 
      O1 > 1 O1 > 2 O1 > 3 
           0      0      0 
      
      
      $m6a
      $m6a$O1
         M22    M23    M24    O22    O23    O24     C1     C2     C1     C2     C1 
           0      0      0      0      0      0      0      0      0      0      0 
          C2 O1 ≤ 1 O1 ≤ 2 O1 ≤ 3 
           0      0      0      0 
      
      
      $m6b
      $m6b$O1
         M22    M23    M24    O22    O23    O24  C1:C2     C1     C2     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1     C2 O1 ≤ 1 O1 ≤ 2 O1 ≤ 3 
           0      0      0      0      0 
      
      
      $m6c
      $m6c$O1
         M22    M23    M24    O22    O23    O24     C1     C2  C1:C2     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
       C1:C2     C1     C2  C1:C2 O1 ≤ 1 O1 ≤ 2 O1 ≤ 3 
           0      0      0      0      0      0      0 
      
      
      $m6d
      $m6d$O1
         M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 M24:C2     C1     C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1     C2     C1     C2 O1 ≤ 1 O1 ≤ 2 O1 ≤ 3 
           0      0      0      0      0      0      0 
      
      
      $m6e
      $m6e$O1
          C1    M22    M23    M24     C2    O22    O23    O24 M22:C2 M23:C2 M24:C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1    M22    M23    M24     C2    O22    O23    O24 M22:C2 M23:C2 M24:C2 
           0      0      0      0      0      0      0      0      0      0      0 
          C1    M22    M23    M24     C2    O22    O23    O24 M22:C2 M23:C2 M24:C2 
           0      0      0      0      0      0      0      0      0      0      0 
      O1 ≤ 1 O1 ≤ 2 O1 ≤ 3 
           0      0      0 
      
      

---

    Code
      lapply(models0, confint)
    Output
      $m0a
      $m0a$O1
             2.5% 97.5%
      O1 > 1    0     0
      O1 > 2    0     0
      O1 > 3    0     0
      
      
      $m0b
      $m0b$O2
             2.5% 97.5%
      O2 > 1    0     0
      O2 > 2    0     0
      O2 > 3    0     0
      
      
      $m1a
      $m1a$O1
             2.5% 97.5%
      C1        0     0
      O1 > 1    0     0
      O1 > 2    0     0
      O1 > 3    0     0
      
      
      $m1b
      $m1b$O2
             2.5% 97.5%
      C1        0     0
      O2 > 1    0     0
      O2 > 2    0     0
      O2 > 3    0     0
      
      
      $m2a
      $m2a$O1
             2.5% 97.5%
      C2        0     0
      O1 > 1    0     0
      O1 > 2    0     0
      O1 > 3    0     0
      
      
      $m2b
      $m2b$O2
             2.5% 97.5%
      C2        0     0
      O2 > 1    0     0
      O2 > 2    0     0
      O2 > 3    0     0
      
      
      $m3a
      $m3a$C1
                  2.5% 97.5%
      (Intercept)    0     0
      O1.L           0     0
      O1.Q           0     0
      O1.C           0     0
      sigma_C1       0     0
      
      
      $m3b
      $m3b$C1
                  2.5% 97.5%
      (Intercept)    0     0
      O22            0     0
      O23            0     0
      O24            0     0
      sigma_C1       0     0
      
      
      $m4a
      $m4a$O1
                       2.5% 97.5%
      M22                 0     0
      M23                 0     0
      M24                 0     0
      O22                 0     0
      O23                 0     0
      O24                 0     0
      abs(C1 - C2)        0     0
      log(C1)             0     0
      O22:abs(C1 - C2)    0     0
      O23:abs(C1 - C2)    0     0
      O24:abs(C1 - C2)    0     0
      O1 > 1              0     0
      O1 > 2              0     0
      O1 > 3              0     0
      
      
      $m4b
      $m4b$O1
                                                                 2.5% 97.5%
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                 0     0
      abs(C1 - C2)                                                  0     0
      log(C1)                                                       0     0
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)    0     0
      O1 > 1                                                        0     0
      O1 > 2                                                        0     0
      O1 > 3                                                        0     0
      
      
      $m5a
      $m5a$O1
             2.5% 97.5%
      M22       0     0
      M23       0     0
      M24       0     0
      O22       0     0
      O23       0     0
      O24       0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      O1 > 1    0     0
      O1 > 2    0     0
      O1 > 3    0     0
      
      
      $m5b
      $m5b$O1
             2.5% 97.5%
      M22       0     0
      M23       0     0
      M24       0     0
      O22       0     0
      O23       0     0
      O24       0     0
      C1:C2     0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      O1 > 1    0     0
      O1 > 2    0     0
      O1 > 3    0     0
      
      
      $m5c
      $m5c$O1
             2.5% 97.5%
      M22       0     0
      M23       0     0
      M24       0     0
      O22       0     0
      O23       0     0
      O24       0     0
      C1        0     0
      C2        0     0
      C1:C2     0     0
      C1        0     0
      C2        0     0
      C1:C2     0     0
      C1        0     0
      C2        0     0
      C1:C2     0     0
      O1 > 1    0     0
      O1 > 2    0     0
      O1 > 3    0     0
      
      
      $m5d
      $m5d$O1
             2.5% 97.5%
      M22       0     0
      M23       0     0
      M24       0     0
      O22       0     0
      O23       0     0
      O24       0     0
      M22:C2    0     0
      M23:C2    0     0
      M24:C2    0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      O1 > 1    0     0
      O1 > 2    0     0
      O1 > 3    0     0
      
      
      $m5e
      $m5e$O1
             2.5% 97.5%
      C1        0     0
      M22       0     0
      M23       0     0
      M24       0     0
      C2        0     0
      O22       0     0
      O23       0     0
      O24       0     0
      M22:C2    0     0
      M23:C2    0     0
      M24:C2    0     0
      C1        0     0
      M22       0     0
      M23       0     0
      M24       0     0
      C2        0     0
      O22       0     0
      O23       0     0
      O24       0     0
      M22:C2    0     0
      M23:C2    0     0
      M24:C2    0     0
      C1        0     0
      M22       0     0
      M23       0     0
      M24       0     0
      C2        0     0
      O22       0     0
      O23       0     0
      O24       0     0
      M22:C2    0     0
      M23:C2    0     0
      M24:C2    0     0
      O1 > 1    0     0
      O1 > 2    0     0
      O1 > 3    0     0
      
      
      $m6a
      $m6a$O1
             2.5% 97.5%
      M22       0     0
      M23       0     0
      M24       0     0
      O22       0     0
      O23       0     0
      O24       0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      O1 ≤ 1    0     0
      O1 ≤ 2    0     0
      O1 ≤ 3    0     0
      
      
      $m6b
      $m6b$O1
             2.5% 97.5%
      M22       0     0
      M23       0     0
      M24       0     0
      O22       0     0
      O23       0     0
      O24       0     0
      C1:C2     0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      O1 ≤ 1    0     0
      O1 ≤ 2    0     0
      O1 ≤ 3    0     0
      
      
      $m6c
      $m6c$O1
             2.5% 97.5%
      M22       0     0
      M23       0     0
      M24       0     0
      O22       0     0
      O23       0     0
      O24       0     0
      C1        0     0
      C2        0     0
      C1:C2     0     0
      C1        0     0
      C2        0     0
      C1:C2     0     0
      C1        0     0
      C2        0     0
      C1:C2     0     0
      O1 ≤ 1    0     0
      O1 ≤ 2    0     0
      O1 ≤ 3    0     0
      
      
      $m6d
      $m6d$O1
             2.5% 97.5%
      M22       0     0
      M23       0     0
      M24       0     0
      O22       0     0
      O23       0     0
      O24       0     0
      M22:C2    0     0
      M23:C2    0     0
      M24:C2    0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      C1        0     0
      C2        0     0
      O1 ≤ 1    0     0
      O1 ≤ 2    0     0
      O1 ≤ 3    0     0
      
      
      $m6e
      $m6e$O1
             2.5% 97.5%
      C1        0     0
      M22       0     0
      M23       0     0
      M24       0     0
      C2        0     0
      O22       0     0
      O23       0     0
      O24       0     0
      M22:C2    0     0
      M23:C2    0     0
      M24:C2    0     0
      C1        0     0
      M22       0     0
      M23       0     0
      M24       0     0
      C2        0     0
      O22       0     0
      O23       0     0
      O24       0     0
      M22:C2    0     0
      M23:C2    0     0
      M24:C2    0     0
      C1        0     0
      M22       0     0
      M23       0     0
      M24       0     0
      C2        0     0
      O22       0     0
      O23       0     0
      O24       0     0
      M22:C2    0     0
      M23:C2    0     0
      M24:C2    0     0
      O1 ≤ 1    0     0
      O1 ≤ 2    0     0
      O1 ≤ 3    0     0
      
      

---

    Code
      lapply(models0, summary)
    Output
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      $m0a
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
           Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m0b
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O2 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
           Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O2 > 1    0  0    0     0          0     NaN    NaN
      O2 > 2    0  0    0     0          0     NaN    NaN
      O2 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m1a
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
         Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      C1    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m1b
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O2 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
         Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      C1    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O2 > 1    0  0    0     0          0     NaN    NaN
      O2 > 2    0  0    0     0          0     NaN    NaN
      O2 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m2a
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
         Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m2b
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O2 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
         Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O2 > 1    0  0    0     0          0     NaN    NaN
      O2 > 2    0  0    0     0          0     NaN    NaN
      O2 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m3a
      
      Bayesian linear model fitted with JointAI
      
      Call:
      lm_imp(formula = C1 ~ O1, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
                  Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      (Intercept)    0  0    0     0          0     NaN    NaN
      O1.L           0  0    0     0          0     NaN    NaN
      O1.Q           0  0    0     0          0     NaN    NaN
      O1.C           0  0    0     0          0     NaN    NaN
      
      Posterior summary of residual std. deviation:
               Mean SD 2.5% 97.5% GR-crit MCE/SD
      sigma_C1    0  0    0     0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 1:10
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m3b
      
      Bayesian linear model fitted with JointAI
      
      Call:
      lm_imp(formula = C1 ~ O2, data = wideDF, n.adapt = 5, n.iter = 10, 
          seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
                  Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      (Intercept)    0  0    0     0          0     NaN    NaN
      O22            0  0    0     0          0     NaN    NaN
      O23            0  0    0     0          0     NaN    NaN
      O24            0  0    0     0          0     NaN    NaN
      
      Posterior summary of residual std. deviation:
               Mean SD 2.5% 97.5% GR-crit MCE/SD
      sigma_C1    0  0    0     0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m4a
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ M2 + O2 * abs(C1 - C2) + log(C1), data = wideDF, 
          n.adapt = 5, n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
                       Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22                 0  0    0     0          0     NaN    NaN
      M23                 0  0    0     0          0     NaN    NaN
      M24                 0  0    0     0          0     NaN    NaN
      O22                 0  0    0     0          0     NaN    NaN
      O23                 0  0    0     0          0     NaN    NaN
      O24                 0  0    0     0          0     NaN    NaN
      abs(C1 - C2)        0  0    0     0          0     NaN    NaN
      log(C1)             0  0    0     0          0     NaN    NaN
      O22:abs(C1 - C2)    0  0    0     0          0     NaN    NaN
      O23:abs(C1 - C2)    0  0    0     0          0     NaN    NaN
      O24:abs(C1 - C2)    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m4b
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ ifelse(as.numeric(O2) > as.numeric(M1), 
          1, 0) * abs(C1 - C2) + log(C1), data = wideDF, n.adapt = 5, 
          n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
                                                                 Mean SD 2.5% 97.5%
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                 0  0    0     0
      abs(C1 - C2)                                                  0  0    0     0
      log(C1)                                                       0  0    0     0
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)    0  0    0     0
                                                                 tail-prob. GR-crit
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                       0     NaN
      abs(C1 - C2)                                                        0     NaN
      log(C1)                                                             0     NaN
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)          0     NaN
                                                                 MCE/SD
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                 NaN
      abs(C1 - C2)                                                  NaN
      log(C1)                                                       NaN
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m5a
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m5b
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      C1:C2      0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m5c
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
                 Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22           0  0    0     0          0     NaN    NaN
      M23           0  0    0     0          0     NaN    NaN
      M24           0  0    0     0          0     NaN    NaN
      O22           0  0    0     0          0     NaN    NaN
      O23           0  0    0     0          0     NaN    NaN
      O24           0  0    0     0          0     NaN    NaN
      O12: C1       0  0    0     0          0     NaN    NaN
      O12: C2       0  0    0     0          0     NaN    NaN
      O12: C1:C2    0  0    0     0          0     NaN    NaN
      O13: C1       0  0    0     0          0     NaN    NaN
      O13: C2       0  0    0     0          0     NaN    NaN
      O13: C1:C2    0  0    0     0          0     NaN    NaN
      O14: C1       0  0    0     0          0     NaN    NaN
      O14: C2       0  0    0     0          0     NaN    NaN
      O14: C1:C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m5d
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      M22:C2     0  0    0     0          0     NaN    NaN
      M23:C2     0  0    0     0          0     NaN    NaN
      M24:C2     0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m5e
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
              M2 * C2 + O2, seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
                  Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O12: C1        0  0    0     0          0     NaN    NaN
      O12: M22       0  0    0     0          0     NaN    NaN
      O12: M23       0  0    0     0          0     NaN    NaN
      O12: M24       0  0    0     0          0     NaN    NaN
      O12: C2        0  0    0     0          0     NaN    NaN
      O12: O22       0  0    0     0          0     NaN    NaN
      O12: O23       0  0    0     0          0     NaN    NaN
      O12: O24       0  0    0     0          0     NaN    NaN
      O12: M22:C2    0  0    0     0          0     NaN    NaN
      O12: M23:C2    0  0    0     0          0     NaN    NaN
      O12: M24:C2    0  0    0     0          0     NaN    NaN
      O13: C1        0  0    0     0          0     NaN    NaN
      O13: M22       0  0    0     0          0     NaN    NaN
      O13: M23       0  0    0     0          0     NaN    NaN
      O13: M24       0  0    0     0          0     NaN    NaN
      O13: C2        0  0    0     0          0     NaN    NaN
      O13: O22       0  0    0     0          0     NaN    NaN
      O13: O23       0  0    0     0          0     NaN    NaN
      O13: O24       0  0    0     0          0     NaN    NaN
      O13: M22:C2    0  0    0     0          0     NaN    NaN
      O13: M23:C2    0  0    0     0          0     NaN    NaN
      O13: M24:C2    0  0    0     0          0     NaN    NaN
      O14: C1        0  0    0     0          0     NaN    NaN
      O14: M22       0  0    0     0          0     NaN    NaN
      O14: M23       0  0    0     0          0     NaN    NaN
      O14: M24       0  0    0     0          0     NaN    NaN
      O14: C2        0  0    0     0          0     NaN    NaN
      O14: O22       0  0    0     0          0     NaN    NaN
      O14: O23       0  0    0     0          0     NaN    NaN
      O14: O24       0  0    0     0          0     NaN    NaN
      O14: M22:C2    0  0    0     0          0     NaN    NaN
      O14: M23:C2    0  0    0     0          0     NaN    NaN
      O14: M24:C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 > 1    0  0    0     0          0     NaN    NaN
      O1 > 2    0  0    0     0          0     NaN    NaN
      O1 > 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m6a
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 ≤ 1    0  0    0     0          0     NaN    NaN
      O1 ≤ 2    0  0    0     0          0     NaN    NaN
      O1 ≤ 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m6b
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      C1:C2      0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 ≤ 1    0  0    0     0          0     NaN    NaN
      O1 ≤ 2    0  0    0     0          0     NaN    NaN
      O1 ≤ 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m6c
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
                 Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22           0  0    0     0          0     NaN    NaN
      M23           0  0    0     0          0     NaN    NaN
      M24           0  0    0     0          0     NaN    NaN
      O22           0  0    0     0          0     NaN    NaN
      O23           0  0    0     0          0     NaN    NaN
      O24           0  0    0     0          0     NaN    NaN
      O12: C1       0  0    0     0          0     NaN    NaN
      O12: C2       0  0    0     0          0     NaN    NaN
      O12: C1:C2    0  0    0     0          0     NaN    NaN
      O13: C1       0  0    0     0          0     NaN    NaN
      O13: C2       0  0    0     0          0     NaN    NaN
      O13: C1:C2    0  0    0     0          0     NaN    NaN
      O14: C1       0  0    0     0          0     NaN    NaN
      O14: C2       0  0    0     0          0     NaN    NaN
      O14: C1:C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 ≤ 1    0  0    0     0          0     NaN    NaN
      O1 ≤ 2    0  0    0     0          0     NaN    NaN
      O1 ≤ 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m6d
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
              C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)
      
      
      Posterior summary:
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      M22:C2     0  0    0     0          0     NaN    NaN
      M23:C2     0  0    0     0          0     NaN    NaN
      M24:C2     0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 ≤ 1    0  0    0     0          0     NaN    NaN
      O1 ≤ 2    0  0    0     0          0     NaN    NaN
      O1 ≤ 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      
      $m6e
      
      Bayesian cumulative logit model fitted with JointAI
      
      Call:
      clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
          n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
              M2 * C2 + O2, rev = "O1", seed = 2020, warn = FALSE, 
          mess = FALSE)
      
      
      Posterior summary:
                  Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O12: C1        0  0    0     0          0     NaN    NaN
      O12: M22       0  0    0     0          0     NaN    NaN
      O12: M23       0  0    0     0          0     NaN    NaN
      O12: M24       0  0    0     0          0     NaN    NaN
      O12: C2        0  0    0     0          0     NaN    NaN
      O12: O22       0  0    0     0          0     NaN    NaN
      O12: O23       0  0    0     0          0     NaN    NaN
      O12: O24       0  0    0     0          0     NaN    NaN
      O12: M22:C2    0  0    0     0          0     NaN    NaN
      O12: M23:C2    0  0    0     0          0     NaN    NaN
      O12: M24:C2    0  0    0     0          0     NaN    NaN
      O13: C1        0  0    0     0          0     NaN    NaN
      O13: M22       0  0    0     0          0     NaN    NaN
      O13: M23       0  0    0     0          0     NaN    NaN
      O13: M24       0  0    0     0          0     NaN    NaN
      O13: C2        0  0    0     0          0     NaN    NaN
      O13: O22       0  0    0     0          0     NaN    NaN
      O13: O23       0  0    0     0          0     NaN    NaN
      O13: O24       0  0    0     0          0     NaN    NaN
      O13: M22:C2    0  0    0     0          0     NaN    NaN
      O13: M23:C2    0  0    0     0          0     NaN    NaN
      O13: M24:C2    0  0    0     0          0     NaN    NaN
      O14: C1        0  0    0     0          0     NaN    NaN
      O14: M22       0  0    0     0          0     NaN    NaN
      O14: M23       0  0    0     0          0     NaN    NaN
      O14: M24       0  0    0     0          0     NaN    NaN
      O14: C2        0  0    0     0          0     NaN    NaN
      O14: O22       0  0    0     0          0     NaN    NaN
      O14: O23       0  0    0     0          0     NaN    NaN
      O14: O24       0  0    0     0          0     NaN    NaN
      O14: M22:C2    0  0    0     0          0     NaN    NaN
      O14: M23:C2    0  0    0     0          0     NaN    NaN
      O14: M24:C2    0  0    0     0          0     NaN    NaN
      
      Posterior summary of the intercepts:
             Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O1 ≤ 1    0  0    0     0          0     NaN    NaN
      O1 ≤ 2    0  0    0     0          0     NaN    NaN
      O1 ≤ 3    0  0    0     0          0     NaN    NaN
      
      
      MCMC settings:
      Iterations = 6:15
      Sample size per chain = 10 
      Thinning interval = 1 
      Number of chains = 3 
      
      Number of observations: 100 
      

---

    Code
      lapply(models0, function(x) coef(summary(x)))
    Output
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      [1] "No variability observed in a component. Setting batch size to 1"
      $m0a
      $m0a$O1
           Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      
      
      $m0b
      $m0b$O2
           Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      
      
      $m1a
      $m1a$O1
         Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      C1    0  0    0     0          0     NaN    NaN
      
      
      $m1b
      $m1b$O2
         Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      C1    0  0    0     0          0     NaN    NaN
      
      
      $m2a
      $m2a$O1
         Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      C2    0  0    0     0          0     NaN    NaN
      
      
      $m2b
      $m2b$O2
         Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      C2    0  0    0     0          0     NaN    NaN
      
      
      $m3a
      $m3a$C1
                  Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      (Intercept)    0  0    0     0          0     NaN    NaN
      O1.L           0  0    0     0          0     NaN    NaN
      O1.Q           0  0    0     0          0     NaN    NaN
      O1.C           0  0    0     0          0     NaN    NaN
      
      
      $m3b
      $m3b$C1
                  Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      (Intercept)    0  0    0     0          0     NaN    NaN
      O22            0  0    0     0          0     NaN    NaN
      O23            0  0    0     0          0     NaN    NaN
      O24            0  0    0     0          0     NaN    NaN
      
      
      $m4a
      $m4a$O1
                       Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22                 0  0    0     0          0     NaN    NaN
      M23                 0  0    0     0          0     NaN    NaN
      M24                 0  0    0     0          0     NaN    NaN
      O22                 0  0    0     0          0     NaN    NaN
      O23                 0  0    0     0          0     NaN    NaN
      O24                 0  0    0     0          0     NaN    NaN
      abs(C1 - C2)        0  0    0     0          0     NaN    NaN
      log(C1)             0  0    0     0          0     NaN    NaN
      O22:abs(C1 - C2)    0  0    0     0          0     NaN    NaN
      O23:abs(C1 - C2)    0  0    0     0          0     NaN    NaN
      O24:abs(C1 - C2)    0  0    0     0          0     NaN    NaN
      
      
      $m4b
      $m4b$O1
                                                                 Mean SD 2.5% 97.5%
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                 0  0    0     0
      abs(C1 - C2)                                                  0  0    0     0
      log(C1)                                                       0  0    0     0
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)    0  0    0     0
                                                                 tail-prob. GR-crit
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                       0     NaN
      abs(C1 - C2)                                                        0     NaN
      log(C1)                                                             0     NaN
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)          0     NaN
                                                                 MCE/SD
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0)                 NaN
      abs(C1 - C2)                                                  NaN
      log(C1)                                                       NaN
      ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2)    NaN
      
      
      $m5a
      $m5a$O1
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      
      $m5b
      $m5b$O1
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      C1:C2      0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      
      $m5c
      $m5c$O1
                 Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22           0  0    0     0          0     NaN    NaN
      M23           0  0    0     0          0     NaN    NaN
      M24           0  0    0     0          0     NaN    NaN
      O22           0  0    0     0          0     NaN    NaN
      O23           0  0    0     0          0     NaN    NaN
      O24           0  0    0     0          0     NaN    NaN
      O12: C1       0  0    0     0          0     NaN    NaN
      O12: C2       0  0    0     0          0     NaN    NaN
      O12: C1:C2    0  0    0     0          0     NaN    NaN
      O13: C1       0  0    0     0          0     NaN    NaN
      O13: C2       0  0    0     0          0     NaN    NaN
      O13: C1:C2    0  0    0     0          0     NaN    NaN
      O14: C1       0  0    0     0          0     NaN    NaN
      O14: C2       0  0    0     0          0     NaN    NaN
      O14: C1:C2    0  0    0     0          0     NaN    NaN
      
      
      $m5d
      $m5d$O1
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      M22:C2     0  0    0     0          0     NaN    NaN
      M23:C2     0  0    0     0          0     NaN    NaN
      M24:C2     0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      
      $m5e
      $m5e$O1
                  Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O12: C1        0  0    0     0          0     NaN    NaN
      O12: M22       0  0    0     0          0     NaN    NaN
      O12: M23       0  0    0     0          0     NaN    NaN
      O12: M24       0  0    0     0          0     NaN    NaN
      O12: C2        0  0    0     0          0     NaN    NaN
      O12: O22       0  0    0     0          0     NaN    NaN
      O12: O23       0  0    0     0          0     NaN    NaN
      O12: O24       0  0    0     0          0     NaN    NaN
      O12: M22:C2    0  0    0     0          0     NaN    NaN
      O12: M23:C2    0  0    0     0          0     NaN    NaN
      O12: M24:C2    0  0    0     0          0     NaN    NaN
      O13: C1        0  0    0     0          0     NaN    NaN
      O13: M22       0  0    0     0          0     NaN    NaN
      O13: M23       0  0    0     0          0     NaN    NaN
      O13: M24       0  0    0     0          0     NaN    NaN
      O13: C2        0  0    0     0          0     NaN    NaN
      O13: O22       0  0    0     0          0     NaN    NaN
      O13: O23       0  0    0     0          0     NaN    NaN
      O13: O24       0  0    0     0          0     NaN    NaN
      O13: M22:C2    0  0    0     0          0     NaN    NaN
      O13: M23:C2    0  0    0     0          0     NaN    NaN
      O13: M24:C2    0  0    0     0          0     NaN    NaN
      O14: C1        0  0    0     0          0     NaN    NaN
      O14: M22       0  0    0     0          0     NaN    NaN
      O14: M23       0  0    0     0          0     NaN    NaN
      O14: M24       0  0    0     0          0     NaN    NaN
      O14: C2        0  0    0     0          0     NaN    NaN
      O14: O22       0  0    0     0          0     NaN    NaN
      O14: O23       0  0    0     0          0     NaN    NaN
      O14: O24       0  0    0     0          0     NaN    NaN
      O14: M22:C2    0  0    0     0          0     NaN    NaN
      O14: M23:C2    0  0    0     0          0     NaN    NaN
      O14: M24:C2    0  0    0     0          0     NaN    NaN
      
      
      $m6a
      $m6a$O1
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      
      $m6b
      $m6b$O1
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      C1:C2      0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      
      $m6c
      $m6c$O1
                 Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22           0  0    0     0          0     NaN    NaN
      M23           0  0    0     0          0     NaN    NaN
      M24           0  0    0     0          0     NaN    NaN
      O22           0  0    0     0          0     NaN    NaN
      O23           0  0    0     0          0     NaN    NaN
      O24           0  0    0     0          0     NaN    NaN
      O12: C1       0  0    0     0          0     NaN    NaN
      O12: C2       0  0    0     0          0     NaN    NaN
      O12: C1:C2    0  0    0     0          0     NaN    NaN
      O13: C1       0  0    0     0          0     NaN    NaN
      O13: C2       0  0    0     0          0     NaN    NaN
      O13: C1:C2    0  0    0     0          0     NaN    NaN
      O14: C1       0  0    0     0          0     NaN    NaN
      O14: C2       0  0    0     0          0     NaN    NaN
      O14: C1:C2    0  0    0     0          0     NaN    NaN
      
      
      $m6d
      $m6d$O1
              Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      M22        0  0    0     0          0     NaN    NaN
      M23        0  0    0     0          0     NaN    NaN
      M24        0  0    0     0          0     NaN    NaN
      O22        0  0    0     0          0     NaN    NaN
      O23        0  0    0     0          0     NaN    NaN
      O24        0  0    0     0          0     NaN    NaN
      M22:C2     0  0    0     0          0     NaN    NaN
      M23:C2     0  0    0     0          0     NaN    NaN
      M24:C2     0  0    0     0          0     NaN    NaN
      O12: C1    0  0    0     0          0     NaN    NaN
      O12: C2    0  0    0     0          0     NaN    NaN
      O13: C1    0  0    0     0          0     NaN    NaN
      O13: C2    0  0    0     0          0     NaN    NaN
      O14: C1    0  0    0     0          0     NaN    NaN
      O14: C2    0  0    0     0          0     NaN    NaN
      
      
      $m6e
      $m6e$O1
                  Mean SD 2.5% 97.5% tail-prob. GR-crit MCE/SD
      O12: C1        0  0    0     0          0     NaN    NaN
      O12: M22       0  0    0     0          0     NaN    NaN
      O12: M23       0  0    0     0          0     NaN    NaN
      O12: M24       0  0    0     0          0     NaN    NaN
      O12: C2        0  0    0     0          0     NaN    NaN
      O12: O22       0  0    0     0          0     NaN    NaN
      O12: O23       0  0    0     0          0     NaN    NaN
      O12: O24       0  0    0     0          0     NaN    NaN
      O12: M22:C2    0  0    0     0          0     NaN    NaN
      O12: M23:C2    0  0    0     0          0     NaN    NaN
      O12: M24:C2    0  0    0     0          0     NaN    NaN
      O13: C1        0  0    0     0          0     NaN    NaN
      O13: M22       0  0    0     0          0     NaN    NaN
      O13: M23       0  0    0     0          0     NaN    NaN
      O13: M24       0  0    0     0          0     NaN    NaN
      O13: C2        0  0    0     0          0     NaN    NaN
      O13: O22       0  0    0     0          0     NaN    NaN
      O13: O23       0  0    0     0          0     NaN    NaN
      O13: O24       0  0    0     0          0     NaN    NaN
      O13: M22:C2    0  0    0     0          0     NaN    NaN
      O13: M23:C2    0  0    0     0          0     NaN    NaN
      O13: M24:C2    0  0    0     0          0     NaN    NaN
      O14: C1        0  0    0     0          0     NaN    NaN
      O14: M22       0  0    0     0          0     NaN    NaN
      O14: M23       0  0    0     0          0     NaN    NaN
      O14: M24       0  0    0     0          0     NaN    NaN
      O14: C2        0  0    0     0          0     NaN    NaN
      O14: O22       0  0    0     0          0     NaN    NaN
      O14: O23       0  0    0     0          0     NaN    NaN
      O14: O24       0  0    0     0          0     NaN    NaN
      O14: M22:C2    0  0    0     0          0     NaN    NaN
      O14: M23:C2    0  0    0     0          0     NaN    NaN
      O14: M24:C2    0  0    0     0          0     NaN    NaN
      
      

