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

INPUT INSTRUCTIONS

  ! SCRIPT NAME        : ctVCut4d  (cb)
  ! GOAL                : To evaluate best model for variance components A D E
  ! DATA                : ordinal
  ! INPUT                : contingency tables
  ! UNI/BI/MULTI        : uni
  ! DATA-GROUPS        : MZM DZM MZF DZF
  ! MEANS MODEL        : -
  ! VARIANCE COVARIANCE MODEL(S)        :
  ! 1. different prevalences for males and females, ADE for males, KLM for females
  ! 2. same prevalences for males and females, ADE for males, KLM for females
  ! 3. same prevalences for males and females, ADE= KLM for males and females
  ! 4. same prevalences for males and females, AE= KM for males and females
  ! 5. same prevalences for males and females, E= M for males and females
  ! 6. different prevalences for males and females, ADE= KLM for males and females
  ! 7. different prevalences for males and females, AE= KM for males and females
  ! 8. different prevalences for males and females, E= M for males and females

  data: file is ct4.dat;

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

  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 constraint:

    new(a d e x w z);
    a=x*x;
    d=w*w;
    e=1-x*x-w*w;
    z=sqrt(1-x*x-w*w);
    mzmc=x*x+w*w;
    dzmc=0.5*x*x+w*w;

    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+0.25*t*t;

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

  ! Uncomment for Model ADE=KLM
  ! a=k;
  ! d=l;

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

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

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



INPUT READING TERMINATED NORMALLY




SUMMARY OF ANALYSIS

Number of groups                                                 4
Number of observations
   Group MZM                                                   243
   Group DZM                                                   137
   Group MZF                                                   620
   Group DZF                                                   317
Number of patterns
   Group MZM                                                     4
   Group DZM                                                     4
   Group MZF                                                     4
   Group DZF                                                     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                                    0.500D-04
Maximum number of steepest descent iterations                   20
Parameterization                                             DELTA

Input data file(s)
  ct4.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



THE MODEL ESTIMATION TERMINATED NORMALLY



TESTS OF MODEL FIT

Chi-Square Test of Model Fit

          Value                              5.325*
          Degrees of Freedom                     6
          P-Value                           0.5029

Chi-Square Contributions From Each Group

          MZM                                0.768
          DZM                                0.721
          MZF                                0.501
          DZF                                3.334

*   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                            167.776
          Degrees of Freedom                     4
          P-Value                           0.0000

CFI/TLI

          CFI                                1.000
          TLI                                1.003

Number of Free Parameters                        6

RMSEA (Root Mean Square Error Of Approximation)

          Estimate                           0.000

WRMR (Weighted Root Mean Square Residual)

          Value                              1.268



MODEL RESULTS

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

Group MZM

 Y1       WITH
    Y2                 0.633      0.138      4.584      0.000

 Thresholds
    Y1$1               1.548      0.080     19.411      0.000
    Y2$1               1.548      0.080     19.411      0.000

Group DZM

 Y1       WITH
    Y2                 0.316      0.291      1.088      0.277

 Thresholds
    Y1$1               1.548      0.080     19.411      0.000
    Y2$1               1.548      0.080     19.411      0.000

Group MZF

 Y1       WITH
    Y2                 0.647      0.055     11.703      0.000

 Thresholds
    Y1$1               0.958      0.040     24.225      0.000
    Y2$1               0.958      0.040     24.225      0.000

Group DZF

 Y1       WITH
    Y2                 0.323      0.112      2.883      0.004

 Thresholds
    Y1$1               0.958      0.040     24.225      0.000
    Y2$1               0.958      0.040     24.225      0.000

 New/Additional Parameters
    A                  0.633      0.644      0.983      0.326
    D                  0.000      0.598      0.000      1.000
    E                  0.367      0.138      2.659      0.008
    X                  0.796      0.405      1.966      0.049
    W                 -0.007     42.398      0.000      1.000
    Z                  0.606      0.114      5.318      0.000
    K                  0.645      0.451      1.428      0.153
    L                  0.002      0.461      0.005      0.996
    M                  0.353      0.055      6.381      0.000
    S                  0.803      0.281      2.856      0.004
    T                  0.050      4.626      0.011      0.991
    U                  0.594      0.047     12.762      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.422E-06
       (ratio of smallest to largest eigenvalue)


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



MUTHEN & MUTHEN
3463 Stoner Ave.
Los Angeles, CA  90066

Tel: (310) 391-9971
Fax: (310) 391-8971
Web: www.StatModel.com
Support: Support@StatModel.com

Copyright (c) 1998-2010 Muthen & Muthen

Back to the list of genetics examples