```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

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
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Los Angeles, CA  90066

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Web: www.StatModel.com
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Copyright (c) 1998-2010 Muthen & Muthen
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