*******EDITED OUPUT*************** Mplus 3.12 MUTHEN & MUTHEN 02/06/2006 12:48 PM INPUT INSTRUCTIONS Title: Muthen & Curran (1977) method, two group analysis with interaction data: file = epilepsy.dat; variable: names = id tx age y0 y1 y2 y3 y4; usev = y0-y4; useobs = id ne 49; Grouping is tx (0=control 1=treat); define: y0 = y0/8; y1 = y1/2; y2 = y2/2; y3 = y3/2; y4 = y4/2; analysis: model: i s | y0@0 y1@1 y2@2 y3@3 y4@4; i t | y0@0 y1@1 y2@2 y3@3 y4@4; [y0-y4] (1); [i@0]; i(2); s(3); i with s (4); [s] (5); t@0; y0-y3 pwith y1-y4; t on i; Model control: [s] (5); t on i@0; [t@0]; output: sampstat modindices(3.84); plot: type = plot3; series = y1-y4(*); INPUT READING TERMINATED NORMALLY Muthen & Curran (1977) method, two group analysis with interaction SUMMARY OF ANALYSIS Number of groups 2 Number of observations Group CONTROL 28 Group TREAT 30 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous Y0 Y1 Y2 Y3 Y4 Continuous latent variables I S T Variables with special functions Grouping variable TX Input data file(s) epilepsy.dat Input data format FREE THE MODEL ESTIMATION TERMINATED NORMALLY WARNING: THE RESIDUAL COVARIANCE MATRIX (THETA) IN GROUP CONTROL IS NOT POSITIVE DEFINITE. THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO OBSERVED VARIABLES. CHECK THE RESULTS SECTION FOR MORE INFORMATION. PROBLEM INVOLVING VARIABLE Y0. WARNING: THE RESIDUAL COVARIANCE MATRIX (THETA) IN GROUP TREAT IS NOT POSITIVE DEFINITE. THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO OBSERVED VARIABLES. CHECK THE RESULTS SECTION FOR MORE INFORMATION. PROBLEM INVOLVING VARIABLE Y0. TESTS OF MODEL FIT Chi-Square Test of Model Fit Value 14.829 Degrees of Freedom 15 P-Value 0.4638 Chi-Square Group Contributions CONTROL 5.842 TREAT 8.987 Chi-Square Test of Model Fit for the Baseline Model Value 221.028 Degrees of Freedom 20 P-Value 0.0000 CFI/TLI CFI 1.000 TLI 1.001 Loglikelihood H0 Value -662.381 H1 Value -654.966 Information Criteria Number of Free Parameters 25 Akaike (AIC) 1374.761 Bayesian (BIC) 1426.272 Sample-Size Adjusted BIC 1347.669 (n* = (n + 2) / 24) RMSEA (Root Mean Square Error Of Approximation) Estimate 0.000 90 Percent C.I. 0.000 0.174 SRMR (Standardized Root Mean Square Residual) Value 0.200 MODEL RESULTS Estimates S.E. Est./S.E. Group CONTROL I | Y0 1.000 0.000 0.000 Y1 1.000 0.000 0.000 Y2 1.000 0.000 0.000 Y3 1.000 0.000 0.000 Y4 1.000 0.000 0.000 S | Y0 0.000 0.000 0.000 Y1 1.000 0.000 0.000 Y2 2.000 0.000 0.000 Y3 3.000 0.000 0.000 Y4 4.000 0.000 0.000 T | Y0 0.000 0.000 0.000 Y1 1.000 0.000 0.000 Y2 2.000 0.000 0.000 Y3 3.000 0.000 0.000 Y4 4.000 0.000 0.000 T ON I 0.000 0.000 0.000 I WITH S -0.195 0.438 -0.444 Y0 WITH Y1 0.417 1.233 0.339 Y1 WITH Y2 2.788 1.584 1.760 Y2 WITH Y3 6.168 2.419 2.550 Y3 WITH Y4 5.461 2.669 2.046 Means I 0.000 0.000 0.000 S 0.037 0.094 0.395 Intercepts Y0 3.479 0.341 10.203 Y1 3.479 0.341 10.203 Y2 3.479 0.341 10.203 Y3 3.479 0.341 10.203 Y4 3.479 0.341 10.203 T 0.000 0.000 0.000 Variances I 8.068 1.842 4.380 S 0.283 0.121 2.331 Residual Variances Y0 -0.357 1.261 -0.283 Y1 12.675 3.768 3.364 Y2 4.273 1.277 3.346 Y3 40.584 10.860 3.737 Y4 0.814 1.526 0.533 T 0.000 0.000 0.000 Group TREAT I | Y0 1.000 0.000 0.000 Y1 1.000 0.000 0.000 Y2 1.000 0.000 0.000 Y3 1.000 0.000 0.000 Y4 1.000 0.000 0.000 S | Y0 0.000 0.000 0.000 Y1 1.000 0.000 0.000 Y2 2.000 0.000 0.000 Y3 3.000 0.000 0.000 Y4 4.000 0.000 0.000 T | Y0 0.000 0.000 0.000 Y1 1.000 0.000 0.000 Y2 2.000 0.000 0.000 Y3 3.000 0.000 0.000 Y4 4.000 0.000 0.000 T ON I -0.106 0.054 -1.975 I WITH S -0.195 0.438 -0.444 Y0 WITH Y1 -3.067 1.437 -2.135 Y1 WITH Y2 -1.918 0.991 -1.935 Y2 WITH Y3 2.564 1.079 2.376 Y3 WITH Y4 0.179 0.857 0.209 Means I 0.000 0.000 0.000 S 0.037 0.094 0.395 Intercepts Y0 3.479 0.341 10.203 Y1 3.479 0.341 10.203 Y2 3.479 0.341 10.203 Y3 3.479 0.341 10.203 Y4 3.479 0.341 10.203 T -0.278 0.112 -2.477 Variances I 8.068 1.842 4.380 S 0.283 0.121 2.331 Residual Variances Y0 -1.031 1.604 -0.643 Y1 1.603 1.232 1.301 Y2 4.979 1.342 3.710 Y3 6.661 1.871 3.560 Y4 -1.742 1.218 -1.431 T 0.000 0.000 0.000 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) 1998-2005 Muthen & Muthen