Mplus VERSION 8.7 (Mac) MUTHEN & MUTHEN 10/21/2021 10:47 PM INPUT INSTRUCTIONS TITLE: this is an example of a CFA with categorical factor indicators DATA: FILE IS ex5.2.dat; VARIABLE: NAMES ARE u1-u6; CATEGORICAL ARE u1-u6; MODEL: f1 BY u1-u3; f2 BY u4-u6; INPUT READING TERMINATED NORMALLY this is an example of a CFA with categorical factor indicators SUMMARY OF ANALYSIS Number of groups 1 Number of observations 500 Number of dependent variables 6 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Binary and ordered categorical (ordinal) U1 U2 U3 U4 U5 U6 Continuous latent variables F1 F2 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) ex5.2.dat Input data format FREE UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES U1 Category 1 0.504 252.000 Category 2 0.496 248.000 U2 Category 1 0.506 253.000 Category 2 0.494 247.000 U3 Category 1 0.496 248.000 Category 2 0.504 252.000 U4 Category 1 0.524 262.000 Category 2 0.476 238.000 U5 Category 1 0.508 254.000 Category 2 0.492 246.000 U6 Category 1 0.510 255.000 Category 2 0.490 245.000 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 13 Chi-Square Test of Model Fit Value 5.482* Degrees of Freedom 8 P-Value 0.7051 * 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 0.040 Probability RMSEA <= .05 0.983 CFI/TLI CFI 1.000 TLI 1.000 Chi-Square Test of Model Fit for the Baseline Model Value 2808.627 Degrees of Freedom 15 P-Value 0.0000 SRMR (Standardized Root Mean Square Residual) Value 0.021 Optimum Function Value for Weighted Least-Squares Estimator Value 0.24587142D-02 MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value F1 BY U1 1.000 0.000 999.000 999.000 U2 1.067 0.043 24.661 0.000 U3 1.001 0.039 25.913 0.000 F2 BY U4 1.000 0.000 999.000 999.000 U5 1.109 0.054 20.482 0.000 U6 1.030 0.047 21.988 0.000 F2 WITH F1 -0.021 0.049 -0.432 0.666 Thresholds U1$1 0.010 0.056 0.179 0.858 U2$1 0.015 0.056 0.268 0.788 U3$1 -0.010 0.056 -0.179 0.858 U4$1 0.060 0.056 1.073 0.283 U5$1 0.020 0.056 0.358 0.721 U6$1 0.025 0.056 0.447 0.655 Variances F1 0.800 0.046 17.439 0.000 F2 0.736 0.052 14.099 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.200E-01 (ratio of smallest to largest eigenvalue) R-SQUARE Observed Residual Variable Estimate Variance U1 0.800 0.200 U2 0.912 0.088 U3 0.802 0.198 U4 0.736 0.264 U5 0.906 0.094 U6 0.781 0.219 Beginning Time: 22:47:54 Ending Time: 22:47:54 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