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

INPUT INSTRUCTIONS

  ! SCRIPT NAME        : ordVCut6c  (cvb)
  ! GOAL                : univariate Mx script for the analysis of one categorical phenotype
  ! DATA                : ordinal
  ! INPUT                : raw data
  ! UNI/BI/MULTI        : uni
  ! DATA-GROUPS        : MZM, DZM, MZF, DZF, DOSMF, DOSFM
  ! MEANS MODEL        : assuming no differences in prevalences across twin1, twin2 and MZ,
  ! VARIANCE COVARIANCE MODEL(S)        : 1. ACE/KLM (sex diffs in variance components), rg-
  !
  ! Evaluated models:
  ! 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 ordraw1.dat;

  variable: names are id y1 y2 zygot age;
            categorical=y1 y2;
            usevar are y1 y2;
            grouping=zygot(1=MZM 2=DZM 3=MZF 4=DZF 5=DOSMF 6=DOSFM);  ! specify the groups
            missing=all(-9); ! specify missing data symbol

  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.
  ! MEANS MODEL	: assuming no differences in prevalences across twin1, twin2 and MZ, DZ, test
*** WARNING
  Input line exceeded 90 characters. Some input may be truncated.
  ! VARIANCE COVARIANCE MODEL(S)	: 1. ACE/KLM (sex diffs in variance components), rg-DOS free
*** 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
  11 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS




SUMMARY OF ANALYSIS

Number of groups                                                 6
Number of observations
   Group MZM                                                   399
   Group DZM                                                   273
   Group MZF                                                   891
   Group DZF                                                   577
   Group DOSMF                                                 381
   Group DOSFM                                                 330

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     ZYGOT

Estimator                                                    WLSMV
Maximum number of iterations                                  1000
Convergence criterion                                    0.100D-05
Maximum number of steepest descent iterations                   20
Maximum number of iterations for H1                           2000
Convergence criterion for H1                             0.100D-03
Parameterization                                             DELTA

Input data file(s)
  ordraw1.dat

Input data format  FREE


SUMMARY OF DATA

   Group MZM
     Number of missing data patterns             3

   Group DZM
     Number of missing data patterns             3

   Group MZF
     Number of missing data patterns             3

   Group DZF
     Number of missing data patterns             3

   Group DOSMF
     Number of missing data patterns             3

   Group DOSFM
     Number of missing data patterns             3


COVARIANCE COVERAGE OF DATA

Minimum covariance coverage value   0.100


     PROPORTION OF DATA PRESENT FOR MZM


           Covariance Coverage
              Y1            Y2
              ________      ________
 Y1             0.827
 Y2             0.609         0.782


     PROPORTION OF DATA PRESENT FOR DZM


           Covariance Coverage
              Y1            Y2
              ________      ________
 Y1             0.744
 Y2             0.498         0.755


     PROPORTION OF DATA PRESENT FOR MZF


           Covariance Coverage
              Y1            Y2
              ________      ________
 Y1             0.856
 Y2             0.694         0.837


     PROPORTION OF DATA PRESENT FOR DZF


           Covariance Coverage
              Y1            Y2
              ________      ________
 Y1             0.792
 Y2             0.549         0.757


     PROPORTION OF DATA PRESENT FOR DOSMF


           Covariance Coverage
              Y1            Y2
              ________      ________
 Y1             0.633
 Y2             0.454         0.822


     PROPORTION OF DATA PRESENT FOR DOSFM


           Covariance Coverage
              Y1            Y2
              ________      ________
 Y1             0.845
 Y2             0.424         0.579


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

  Group MZM
    Y1
      Category 1    0.952      314.000
      Category 2    0.048       16.000
    Y2
      Category 1    0.933      291.000
      Category 2    0.067       21.000

  Group DZM
    Y1
      Category 1    0.946      192.000
      Category 2    0.054       11.000
    Y2
      Category 1    0.937      193.000
      Category 2    0.063       13.000

  Group MZF
    Y1
      Category 1    0.814      621.000
      Category 2    0.186      142.000
    Y2
      Category 1    0.822      613.000
      Category 2    0.178      133.000

  Group DZF
    Y1
      Category 1    0.838      383.000
      Category 2    0.162       74.000
    Y2
      Category 1    0.812      355.000
      Category 2    0.188       82.000

  Group DOSMF
    Y1
      Category 1    0.909      219.000
      Category 2    0.091       22.000
    Y2
      Category 1    0.812      254.000
      Category 2    0.188       59.000

  Group DOSFM
    Y1
      Category 1    0.857      239.000
      Category 2    0.143       40.000
    Y2
      Category 1    0.916      175.000
      Category 2    0.084       16.000


     WARNING:  THE BIVARIATE TABLE OF Y2 AND Y1 HAS AN EMPTY CELL.


THE MODEL ESTIMATION TERMINATED NORMALLY



TESTS OF MODEL FIT

Chi-Square Test of Model Fit

          Value                              8.248*
          Degrees of Freedom                    11
          P-Value                           0.6909

Chi-Square Contributions From Each Group

          MZM                                1.680
          DZM                                0.785
          MZF                                0.358
          DZF                                0.914
          DOSMF                              1.957
          DOSFM                              2.555

*   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                            176.183
          Degrees of Freedom                     6
          P-Value                           0.0000

CFI/TLI

          CFI                                1.000
          TLI                                1.009

Number of Free Parameters                        7

RMSEA (Root Mean Square Error Of Approximation)

          Estimate                           0.000

WRMR (Weighted Root Mean Square Residual)

          Value                              1.804



MODEL RESULTS

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

Group MZM

 Y1       WITH
    Y2                 0.642      0.136      4.704      0.000

 Thresholds
    Y1$1               1.494      0.052     28.512      0.000
    Y2$1               1.494      0.052     28.512      0.000

Group DZM

 Y1       WITH
    Y2                 0.321      0.068      4.704      0.000

 Thresholds
    Y1$1               1.494      0.052     28.512      0.000
    Y2$1               1.494      0.052     28.512      0.000

Group MZF

 Y1       WITH
    Y2                 0.651      0.053     12.179      0.000

 Thresholds
    Y1$1               0.926      0.029     31.533      0.000
    Y2$1               0.926      0.029     31.533      0.000

Group DZF

 Y1       WITH
    Y2                 0.326      0.027     12.179      0.000

 Thresholds
    Y1$1               0.926      0.029     31.533      0.000
    Y2$1               0.926      0.029     31.533      0.000

Group DOSMF

 Y1       WITH
    Y2                 0.305      0.131      2.330      0.020

 Thresholds
    Y1$1               1.494      0.052     28.512      0.000
    Y2$1               0.926      0.029     31.533      0.000

Group DOSFM

 Y1       WITH
    Y2                 0.305      0.131      2.330      0.020

 Thresholds
    Y1$1               0.926      0.029     31.533      0.000
    Y2$1               1.494      0.052     28.512      0.000

 New/Additional Parameters
    A                  0.642      0.136      4.704      0.000
    C                  0.000      0.000   4107.964      0.000
    E                  0.358      0.136      2.626      0.009
    X                  0.801      0.085      9.409      0.000
    Y                  0.000      0.000   8215.929      0.000
    Z                  0.599      0.114      5.253      0.000
    K                  0.651      0.053     12.179      0.000
    L                  0.000      0.000  23147.162      0.000
    M                  0.349      0.053      6.527      0.000
    S                  0.807      0.033     24.357      0.000
    T                  0.000      0.000  46294.320      0.000
    U                  0.591      0.045     13.054      0.000
    F                  0.472      0.209      2.252      0.024


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.100E-05
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  22:57:40
        Ending Time:  22:57:41
       Elapsed Time:  00:00:01



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