Mplus VERSION 6
MUTHEN & MUTHEN
04/25/2010  10:57 PM

INPUT INSTRUCTIONS

  ! SCRIPT NAME        : ctVCut6c  (cb)
  ! GOAL                : To evaluate best model for variance components A C E
  ! DATA                : ordinal
  ! INPUT                : contingency tables
  ! UNI/BI/MULTI        : uni
  ! DATA-GROUPS        : MZM DZM MZF DZF DOSMF DOSFM
  ! MEANS MODEL        : -
  ! VARIANCE COVARIANCE MODEL(S)        :
  ! 1. different prevalences for males and females, rg free for DOS, ACE for males, KLM for
  ! 2. same prevalences for males and females, rg free for DOS, ACE for males, KLM for femal
  ! 3. same prevalences for males and females, rg fixed at 0.5 for DOS, ACE for males, KLM f
  ! 4. same prevalences for males and females, rg fixed at 0.5 for DOS, ACE= KLM for males a
  ! 5. same prevalences for males and females, rg fixed at 0.5 for DOS, AE= KM for males and
  ! 6. same prevalences for males and females, rg fixed at 0.5 for DOS, CE= LM for males and
  ! 7. same prevalences for males and females, rg fixed at 0.5 for DOS, E= M for males and f
  ! 8. different prevalences for males and females, rg fixed at 0.5 for DOS, ACE for males,
  ! 9. different prevalences for males and females, rg fixed at 0.5 for DOS, ACE= KLM for ma
  ! 10. different prevalences for males and females, rg fixed at 0.5 for DOS, AE= KM for mal
  ! 11. different prevalences for males and females, rg fixed at 0.5 for DOS, CE= LM for mal
  ! 12. different prevalences for males and females, rg fixed at 0.5 for DOS, E= M for males

  data: file is ct6.dat;

  variable: names are g y1 y2 weight;
            categorical=y1 y2;
            grouping=g(1=MZM 2=DZM 3=MZF 4=DZF 5=DOSMF 6=DOSFM);  ! specify the groups
            freqweight=weight;

  analysis: conv=1e-6;

  model:
       [y1$1] (mt);
       [y2$1] (mt);
       y1 with y2 (mzmc);

  model dzm:
       [y1$1] (mt);
       [y2$1] (mt);
       y1 with y2 (dzmc);

  model mzf:
       [y1$1] (ft);
       [y2$1] (ft);
       y1 with y2 (mzfc);

  model dzf:
       [y1$1] (ft);
       [y2$1] (ft);
       y1 with y2 (dzfc);

  model dosmf:
       [y1$1] (mt);
       [y2$1] (ft);
       y1 with y2 (dosfmc);

  model dosfm:
       [y1$1] (ft);
       [y2$1] (mt);
       y1 with y2 (dosfmc);

  model constraint:

    new(a c e x y z);
    a=x*x;
    c=y*y;
    e=1-x*x-y*y;
    z=sqrt(1-x*x-y*y);
    mzmc=x*x+y*y;
    dzmc=0.5*x*x+y*y;
    x>0; y>0; z>0;

    new(k l m s t u);
    k=s*s;
    l=t*t;
    m=1-s*s-t*t;
    u=sqrt(1-s*s-t*t);
    mzfc=s*s+t*t;
    dzfc=0.5*s*s+t*t;
    s>0; t>0; u>0;

    new(f*0.2); f>0; f<0.5;
    dosfmc=f*x*s+y*t;

  ! Uncomment for same prevalences for males and females
  ! mt=ft;

  ! Uncomment to fix rg to 0.5
  ! f=0.5;

  ! Uncomment for Model ACE=KLM
  ! a=k;
  ! c=l;

  ! Uncomment for Model AE=KM
  ! c=0;

  ! Uncomment for Model CE=LM
  ! a=0;

  ! Uncomment for Model E=M
  ! a=0;
  ! c=0;



*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 1. different prevalences for males and females, rg free for DOS, ACE for males, KLM for f
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 2. same prevalences for males and females, rg free for DOS, ACE for males, KLM for female
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 3. same prevalences for males and females, rg fixed at 0.5 for DOS, ACE for males, KLM fo
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 4. same prevalences for males and females, rg fixed at 0.5 for DOS, ACE= KLM for males an
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 7. same prevalences for males and females, rg fixed at 0.5 for DOS, E= M for males and fe
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 8. different prevalences for males and females, rg fixed at 0.5 for DOS, ACE for males, K
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 9. different prevalences for males and females, rg fixed at 0.5 for DOS, ACE= KLM for mal
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 10. different prevalences for males and females, rg fixed at 0.5 for DOS, AE= KM for male
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! 11. different prevalences for males and females, rg fixed at 0.5 for DOS, CE= LM for male
   9 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS




SUMMARY OF ANALYSIS

Number of groups                                                 6
Number of observations
   Group MZM                                                   243
   Group DZM                                                   137
   Group MZF                                                   620
   Group DZF                                                   317
   Group DOSMF                                                 173
   Group DOSFM                                                 140
Number of patterns
   Group MZM                                                     4
   Group DZM                                                     4
   Group MZF                                                     4
   Group DZF                                                     4
   Group DOSMF                                                   4
   Group DOSFM                                                   4

Number of dependent variables                                    2
Number of independent variables                                  0
Number of continuous latent variables                            0

Observed dependent variables

  Binary and ordered categorical (ordinal)
   Y1          Y2

Variables with special functions

  Grouping variable     G
  Weight variable       WEIGHT

Estimator                                                    WLSMV
Maximum number of iterations                                  1000
Convergence criterion                                    0.100D-05
Maximum number of steepest descent iterations                   20
Parameterization                                             DELTA

Input data file(s)
  ct6.dat

Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

  Group MZM
    Y1
      Category 1    0.951      231.000
      Category 2    0.049       12.000
    Y2
      Category 1    0.934      227.000
      Category 2    0.066       16.000

  Group DZM
    Y1
      Category 1    0.942      129.000
      Category 2    0.058        8.000
    Y2
      Category 1    0.927      127.000
      Category 2    0.073       10.000

  Group MZF
    Y1
      Category 1    0.821      509.000
      Category 2    0.179      111.000
    Y2
      Category 1    0.832      516.000
      Category 2    0.168      104.000

  Group DZF
    Y1
      Category 1    0.864      274.000
      Category 2    0.136       43.000
    Y2
      Category 1    0.817      259.000
      Category 2    0.183       58.000

  Group DOSMF
    Y1
      Category 1    0.908      157.000
      Category 2    0.092       16.000
    Y2
      Category 1    0.809      140.000
      Category 2    0.191       33.000

  Group DOSFM
    Y1
      Category 1    0.879      123.000
      Category 2    0.121       17.000
    Y2
      Category 1    0.914      128.000
      Category 2    0.086       12.000



THE MODEL ESTIMATION TERMINATED NORMALLY



TESTS OF MODEL FIT

Chi-Square Test of Model Fit

          Value                              9.082*
          Degrees of Freedom                    11
          P-Value                           0.6143

Chi-Square Contributions From Each Group

          MZM                                1.462
          DZM                                0.515
          MZF                                0.477
          DZF                                2.536
          DOSMF                              1.687
          DOSFM                              2.405

*   The chi-square value for MLM, MLMV, MLR, ULSMV, WLSM and WLSMV cannot be used
    for chi-square difference testing in the regular way.  MLM, MLR and WLSM
    chi-square difference testing is described on the Mplus website.  MLMV, WLSMV,
    and ULSMV difference testing is done using the DIFFTEST option.

Chi-Square Test of Model Fit for the Baseline Model

          Value                            173.209
          Degrees of Freedom                     6
          P-Value                           0.0000

CFI/TLI

          CFI                                1.000
          TLI                                1.006

Number of Free Parameters                        7

RMSEA (Root Mean Square Error Of Approximation)

          Estimate                           0.000

WRMR (Weighted Root Mean Square Residual)

          Value                              1.873



MODEL RESULTS

                                                    Two-Tailed
                    Estimate       S.E.  Est./S.E.    P-Value

Group MZM

 Y1       WITH
    Y2                 0.633      0.134      4.710      0.000

 Thresholds
    Y1$1               1.478      0.063     23.618      0.000
    Y2$1               1.478      0.063     23.618      0.000

Group DZM

 Y1       WITH
    Y2                 0.316      0.067      4.710      0.000

 Thresholds
    Y1$1               1.478      0.063     23.618      0.000
    Y2$1               1.478      0.063     23.618      0.000

Group MZF

 Y1       WITH
    Y2                 0.647      0.054     12.053      0.000

 Thresholds
    Y1$1               0.963      0.036     26.681      0.000
    Y2$1               0.963      0.036     26.681      0.000

Group DZF

 Y1       WITH
    Y2                 0.324      0.027     12.057      0.000

 Thresholds
    Y1$1               0.963      0.036     26.681      0.000
    Y2$1               0.963      0.036     26.681      0.000

Group DOSMF

 Y1       WITH
    Y2                 0.305      0.131      2.325      0.020

 Thresholds
    Y1$1               1.478      0.063     23.618      0.000
    Y2$1               0.963      0.036     26.681      0.000

Group DOSFM

 Y1       WITH
    Y2                 0.305      0.131      2.325      0.020

 Thresholds
    Y1$1               0.963      0.036     26.681      0.000
    Y2$1               1.478      0.063     23.618      0.000

 New/Additional Parameters
    A                  0.633      0.134      4.710      0.000
    C                  0.000      0.000  *********      0.000
    E                  0.367      0.134      2.734      0.006
    X                  0.795      0.084      9.421      0.000
    Y                  0.000      0.000  *********      0.000
    Z                  0.606      0.111      5.468      0.000
    K                  0.647      0.054     12.048      0.000
    L                  0.000      0.001      0.387      0.699
    M                  0.353      0.054      6.574      0.000
    S                  0.804      0.033     24.096      0.000
    T                  0.015      0.020      0.774      0.439
    U                  0.594      0.045     13.148      0.000
    F                  0.476      0.212      2.247      0.025


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.949E-06
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  22:57:38
        Ending Time:  22:57:39
       Elapsed Time:  00:00:01



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