Mplus VERSION 8.7 (Mac) MUTHEN & MUTHEN 10/21/2021 10:48 PM INPUT INSTRUCTIONS TITLE: this is an example of a linear growth model for a continuous outcome DATA: FILE IS ex6.1.dat; VARIABLE: NAMES ARE y11-y14; MODEL: i s | y11@0 y12@1 y13@2 y14@3; INPUT READING TERMINATED NORMALLY this is an example of a linear growth model for a continuous 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 Continuous Y11 Y12 Y13 Y14 Continuous latent variables I S Estimator ML Information matrix OBSERVED Maximum number of iterations 1000 Convergence criterion 0.500D-04 Maximum number of steepest descent iterations 20 Input data file(s) ex6.1.dat Input data format FREE UNIVARIATE SAMPLE STATISTICS UNIVARIATE HIGHER-ORDER MOMENT DESCRIPTIVE STATISTICS Variable/ Mean/ Skewness/ Minimum/ % with Percentiles Sample Size Variance Kurtosis Maximum Min/Max 20%/60% 40%/80% Median Y11 0.514 -0.170 -2.693 0.20% -0.493 0.237 0.558 500.000 1.449 -0.354 3.598 0.20% 0.813 1.610 Y12 1.566 -0.077 -3.062 0.20% 0.443 1.283 1.560 500.000 1.974 0.003 5.964 0.20% 1.869 2.761 Y13 2.568 -0.031 -2.745 0.20% 1.013 2.106 2.520 500.000 2.931 -0.252 8.428 0.20% 3.051 4.144 Y14 3.601 -0.091 -2.360 0.20% 1.832 3.056 3.612 500.000 4.298 -0.121 9.182 0.20% 4.164 5.335 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 9 Loglikelihood H0 Value -3016.386 H1 Value -3014.089 Information Criteria Akaike (AIC) 6050.772 Bayesian (BIC) 6088.703 Sample-Size Adjusted BIC 6060.137 (n* = (n + 2) / 24) Chi-Square Test of Model Fit Value 4.593 Degrees of Freedom 5 P-Value 0.4675 RMSEA (Root Mean Square Error Of Approximation) Estimate 0.000 90 Percent C.I. 0.000 0.060 Probability RMSEA <= .05 0.894 CFI/TLI CFI 1.000 TLI 1.000 Chi-Square Test of Model Fit for the Baseline Model Value 1439.722 Degrees of Freedom 6 P-Value 0.0000 SRMR (Standardized Root Mean Square Residual) Value 0.010 MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value I | Y11 1.000 0.000 999.000 999.000 Y12 1.000 0.000 999.000 999.000 Y13 1.000 0.000 999.000 999.000 Y14 1.000 0.000 999.000 999.000 S | Y11 0.000 0.000 999.000 999.000 Y12 1.000 0.000 999.000 999.000 Y13 2.000 0.000 999.000 999.000 Y14 3.000 0.000 999.000 999.000 S WITH I 0.133 0.032 4.100 0.000 Means I 0.523 0.051 10.152 0.000 S 1.026 0.025 40.264 0.000 Intercepts Y11 0.000 0.000 999.000 999.000 Y12 0.000 0.000 999.000 999.000 Y13 0.000 0.000 999.000 999.000 Y14 0.000 0.000 999.000 999.000 Variances I 0.989 0.088 11.178 0.000 S 0.224 0.022 10.068 0.000 Residual Variances Y11 0.475 0.058 8.122 0.000 Y12 0.482 0.040 11.980 0.000 Y13 0.473 0.047 10.080 0.000 Y14 0.545 0.083 6.593 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.462E-01 (ratio of smallest to largest eigenvalue) Beginning Time: 22:48:52 Ending Time: 22:48:52 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