Mplus VERSION 8.7 (Mac) MUTHEN & MUTHEN 10/21/2021 10:49 PM INPUT INSTRUCTIONS TITLE: this is an example of a linear growth model for a categorical outcome DATA: FILE IS ex6.4.dat; VARIABLE: NAMES ARE u11-u14; CATEGORICAL ARE u11-u14; MODEL: i s | u11@0 u12@1 u13@2 u14@3; INPUT READING TERMINATED NORMALLY this is an example of a linear growth model for a categorical outcome SUMMARY OF ANALYSIS Number of groups 1 Number of observations 500 Number of dependent variables 4 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Binary and ordered categorical (ordinal) U11 U12 U13 U14 Continuous latent variables I S Estimator WLSMV Maximum number of iterations 1000 Convergence criterion 0.500D-04 Maximum number of steepest descent iterations 20 Parameterization DELTA Link PROBIT Input data file(s) ex6.4.dat Input data format FREE UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES U11 Category 1 0.310 155.000 Category 2 0.690 345.000 U12 Category 1 0.466 233.000 Category 2 0.534 267.000 U13 Category 1 0.624 312.000 Category 2 0.376 188.000 U14 Category 1 0.714 357.000 Category 2 0.286 143.000 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 8 Chi-Square Test of Model Fit Value 1.214* Degrees of Freedom 2 P-Value 0.5449 * 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. RMSEA (Root Mean Square Error Of Approximation) Estimate 0.000 90 Percent C.I. 0.000 0.077 Probability RMSEA <= .05 0.819 CFI/TLI CFI 1.000 TLI 1.000 Chi-Square Test of Model Fit for the Baseline Model Value 296.848 Degrees of Freedom 6 P-Value 0.0000 SRMR (Standardized Root Mean Square Residual) Value 0.016 Optimum Function Value for Weighted Least-Squares Estimator Value 0.78968175D-03 MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value I | U11 1.000 0.000 999.000 999.000 U12 1.000 0.000 999.000 999.000 U13 1.000 0.000 999.000 999.000 U14 1.000 0.000 999.000 999.000 S | U11 0.000 0.000 999.000 999.000 U12 1.000 0.000 999.000 999.000 U13 2.000 0.000 999.000 999.000 U14 3.000 0.000 999.000 999.000 S WITH I -0.007 0.054 -0.132 0.895 Means I 0.000 0.000 999.000 999.000 S -0.407 0.053 -7.680 0.000 Thresholds U11$1 -0.494 0.058 -8.503 0.000 U12$1 -0.494 0.058 -8.503 0.000 U13$1 -0.494 0.058 -8.503 0.000 U14$1 -0.494 0.058 -8.503 0.000 Variances I 0.439 0.114 3.845 0.000 S 0.042 0.035 1.202 0.229 Scales U11 1.000 0.000 999.000 999.000 U12 1.060 0.149 7.133 0.000 U13 1.012 0.192 5.259 0.000 U14 0.772 0.153 5.029 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.496E-03 (ratio of smallest to largest eigenvalue) R-SQUARE Observed Residual Variable Estimate Variance U11 0.439 0.561 U12 0.524 0.424 U13 0.592 0.399 U14 0.461 0.904 Beginning Time: 22:49:25 Ending Time: 22:49:25 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) 1998-2021 Muthen & Muthen