Mplus VERSION 6 MUTHEN & MUTHEN 06/30/2010 4:37 PM INPUT INSTRUCTIONS title: M10 model variable: NAMES ARE y1-y5; data: file=1.dat; analysis: estimator=mlr; convergence=100000000; model: y3 with y2*0; f1 BY y1@1; f1 BY y2*0.599; f1 BY y3*0.814; f1 BY y4*0.893; f1 BY y5*0.818; y1 WITH y2*-0.031; [ y1*0.280 ]; [ y2*0.380 ]; [ y3*0.400 ]; [ y4*0.420 ]; [ y5*0.420 ]; y1*0.167; y2*0.337; y3*0.378; y4*0.385; y5*0.420; f1*0.274; output: tech5; INPUT READING TERMINATED NORMALLY M10 model SUMMARY OF ANALYSIS Number of groups 1 Number of observations 50 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous Y1 Y2 Y3 Y4 Y5 Continuous latent variables F1 Estimator MLR Information matrix OBSERVED Maximum number of iterations 1000 Convergence criterion 0.100D+09 Maximum number of steepest descent iterations 20 Input data file(s) 1.dat Input data format FREE THE MODEL ESTIMATION TERMINATED NORMALLY TESTS OF MODEL FIT Chi-Square Test of Model Fit Value 287.907* Degrees of Freedom 3 P-Value 0.0000 Scaling Correction Factor 0.034 for MLR * 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 43.028 Degrees of Freedom 10 P-Value 0.0000 CFI/TLI CFI 0.000 TLI -27.754 Loglikelihood H0 Value -250.888 H0 Scaling Correction Factor 1.850 for MLR H1 Value -246.017 H1 Scaling Correction Factor 1.578 for MLR Information Criteria Number of Free Parameters 17 Akaike (AIC) 535.776 Bayesian (BIC) 568.281 Sample-Size Adjusted BIC 514.920 (n* = (n + 2) / 24) RMSEA (Root Mean Square Error Of Approximation) Estimate 1.378 90 Percent C.I. 1.246 1.515 Probability RMSEA <= .05 0.000 SRMR (Standardized Root Mean Square Residual) Value 0.072 MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value F1 BY Y1 1.000 0.000 999.000 999.000 Y2 0.599 0.523 1.145 0.252 Y3 0.814 0.600 1.356 0.175 Y4 0.893 0.643 1.390 0.165 Y5 0.818 0.290 2.823 0.005 Y3 WITH Y2 0.000 0.111 0.000 1.000 Y1 WITH Y2 -0.031 0.181 -0.172 0.864 Intercepts Y1 0.280 0.094 2.979 0.003 Y2 0.380 0.093 4.071 0.000 Y3 0.400 0.106 3.780 0.000 Y4 0.420 0.110 3.823 0.000 Y5 0.420 0.110 3.823 0.000 Variances F1 0.274 0.208 1.314 0.189 Residual Variances Y1 0.167 0.132 1.267 0.205 Y2 0.337 0.180 1.876 0.061 Y3 0.378 0.177 2.134 0.033 Y4 0.385 0.206 1.869 0.062 Y5 0.420 0.204 2.061 0.039 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.781E-02 (ratio of smallest to largest eigenvalue) TECHNICAL 5/6 OUTPUT TECHNICAL OUTPUT FROM EM ALGORITHM ITERATIONS FOR THE H1 MODEL ITER FUNCTION ABS CHANGE REL CHANGE 1 0.17631263D+01 2 0.65129262D+00 -1.1118336 -0.6306035 3 0.65129262D+00 -1.1118336 -0.6306035 TECHNICAL OUTPUT FROM QUASI-NEWTON ITERATIONS ITERATIONS USING GRADIENT ITER STEP FUNCTION ABS CHANGE REL CHANGE STEP LENGTH DERIVATIVE ITERATIONS USING QUASI-NEWTON ITER STEP FUNCTION ABS CHANGE REL CHANGE STEP LENGTH DERIVATIVE Beginning Time: 16:37:15 Ending Time: 16:37:15 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) 1998-2010 Muthen & Muthen