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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