Mplus VERSION 6
MUTHEN & MUTHEN
04/25/2010 10:57 PM
INPUT INSTRUCTIONS
TITLE: cat3
mimic with direct effects for dichotomous outcomes
DATA: FILE IS wmimicd.dat;
VARIABLE: NAMES ARE x1-x3 y1-y16;
USEV = y6-y10 x4 x5 x6 x7;
CATEGORICAL = y6-y10;
DEFINE: x4 = 89 - x1;
x6 = 0; if (x2 eq 2) then x6 = 1;
x7 = 0; if (x2 eq 1) then x7 = 1;
x5 = 1; if (x3 eq 2) then x5 = 0;
ANALYSIS: TYPE = MEANSTRUCTURE;
! using meanstructure adds the thresholds for the
! dichotomous outcomes, but is not essential here
ESTIMATOR = WLSMV;
MODEL: f1 BY y6-y10;
f1 ON x4-x7;
y6 ON x5;
! y6 ON x5 is the direct effect
! given that x variables are present, the analysis assumes
! conditional normality of latent response variables given the x's
! in line with probit analysis. this analysis makes less strong
! normality assumptions than using tetrachoric
! and biserial correlations. Given that the model is fitted to
! estimates from probit regressions, the computations are, however,
! more time consuming than when x's are not present, especially
! for large sample sizes (as in this case) and a large number of
! outcome variables.
*** WARNING in ANALYSIS command
Starting with Version 5, TYPE=MEANSTRUCTURE is the default for all
analyses. To remove means from the model, use
MODEL=NOMEANSTRUCTURE in the ANALYSIS command.
1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
cat3
mimic with direct effects for dichotomous outcomes
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 5042
Number of dependent variables 5
Number of independent variables 4
Number of continuous latent variables 1
Observed dependent variables
Binary and ordered categorical (ordinal)
Y6 Y7 Y8 Y9 Y10
Observed independent variables
X4 X5 X6 X7
Continuous latent variables
F1
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)
wmimicd.dat
Input data format FREE
UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES
Y6
Category 1 0.982 4952.000
Category 2 0.018 90.000
Y7
Category 1 0.972 4901.000
Category 2 0.028 141.000
Y8
Category 1 0.986 4970.000
Category 2 0.014 72.000
Y9
Category 1 0.989 4986.000
Category 2 0.011 56.000
Y10
Category 1 0.956 4819.000
Category 2 0.044 223.000
THE MODEL ESTIMATION TERMINATED NORMALLY
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 42.836*
Degrees of Freedom 20
P-Value 0.0021
* 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 2509.264
Degrees of Freedom 30
P-Value 0.0000
CFI/TLI
CFI 0.991
TLI 0.986
Number of Free Parameters 15
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.015
WRMR (Weighted Root Mean Square Residual)
Value 0.906
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
F1 BY
Y6 1.000 0.000 999.000 999.000
Y7 1.071 0.051 20.863 0.000
Y8 1.079 0.053 20.416 0.000
Y9 1.035 0.055 18.731 0.000
Y10 1.010 0.049 20.443 0.000
F1 ON
X4 -0.032 0.012 -2.717 0.007
X5 0.385 0.060 6.389 0.000
X6 0.081 0.059 1.373 0.170
X7 0.097 0.074 1.323 0.186
Y6 ON
X5 0.310 0.103 3.006 0.003
Thresholds
Y6$1 1.250 0.566 2.209 0.027
Y7$1 2.217 0.465 4.768 0.000
Y8$1 1.694 0.629 2.694 0.007
Y9$1 2.050 0.655 3.132 0.002
Y10$1 0.340 0.399 0.853 0.394
Residual Variances
F1 0.663 0.054 12.222 0.000
R-SQUARE
Observed Residual
Variable Estimate Variance
Y6 0.702 0.337
Y7 0.773 0.239
Y8 0.783 0.229
Y9 0.725 0.289
Y10 0.691 0.323
Latent
Variable Estimate
F1 0.065
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.151E-03
(ratio of smallest to largest eigenvalue)
Beginning Time: 22:57:55
Ending Time: 22:57:56
Elapsed Time: 00:00:01
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 table of examples