Mplus VERSION 6.11 MUTHEN & MUTHEN 09/27/2011 12:16 PM INPUT INSTRUCTIONS title: Simulating x-m interaction effect on y using a random slope, saving the data for external Monte Carlo analysis montecarlo: names = y m x; nobs = 400; nreps = 500; repsave = all; save = xmrep*.dat; cutpoints = x(0); model population: x@1; [y*1]; y on x*.4; beta1 | y on m; beta1 on x*.2; [beta1*.5]; beta1@0; [m*2]; m on x*.5; y*.5; m*1; analysis: type = random; model: [y*1] (beta0); y on x*.4 (beta2); beta1 | y on m; beta1 on x*.2 (beta3); [beta1*.5] (beta1); beta1@0; [m*2] (gamma0); m on x*.5 (gamma1); y*.5; m*1; model constraint: new(tie*.35 pie*.25 de*.8); tie=beta1*gamma1+beta3*gamma1; pie=beta1*gamma1; de=beta2+beta3*gamma0; INPUT READING TERMINATED NORMALLY Simulating x-m interaction effect on y using a random slope, saving the data for external Monte Carlo analysis SUMMARY OF ANALYSIS Number of groups 1 Number of observations 400 Number of replications Requested 500 Completed 500 Value of seed 0 Number of dependent variables 2 Number of independent variables 1 Number of continuous latent variables 1 Observed dependent variables Continuous Y M Observed independent variables X Continuous latent variables BETA1 Estimator MLR Information matrix OBSERVED Maximum number of iterations 100 Convergence criterion 0.100D-05 Maximum number of EM iterations 500 Convergence criteria for the EM algorithm Loglikelihood change 0.100D-02 Relative loglikelihood change 0.100D-05 Derivative 0.100D-03 Minimum variance 0.100D-03 Maximum number of steepest descent iterations 20 Optimization algorithm EMA SAMPLE STATISTICS FOR THE FIRST REPLICATION ESTIMATED SAMPLE STATISTICS Means Y M X ________ ________ ________ 1 2.665 2.284 0.540 Covariances Y M X ________ ________ ________ Y 1.161 M 0.789 1.054 X 0.263 0.124 0.248 Correlations Y M X ________ ________ ________ Y 1.000 M 0.713 1.000 X 0.489 0.242 1.000 MODEL FIT INFORMATION Number of Free Parameters 8 Loglikelihood H0 Value Mean -993.100 Std Dev 20.276 Number of successful computations 500 Proportions Percentiles Expected Observed Expected Observed 0.990 0.994 -1040.268 -1039.385 0.980 0.984 -1034.741 -1034.043 0.950 0.960 -1026.452 -1024.972 0.900 0.900 -1019.086 -1019.150 0.800 0.790 -1010.164 -1011.921 0.700 0.682 -1003.733 -1004.388 0.500 0.514 -993.100 -992.717 0.300 0.296 -982.468 -982.832 0.200 0.208 -976.036 -975.716 0.100 0.100 -967.115 -967.459 0.050 0.056 -959.749 -957.971 0.020 0.018 -951.460 -952.305 0.010 0.010 -945.933 -947.451 Information Criteria Akaike (AIC) Mean 2002.201 Std Dev 40.551 Number of successful computations 500 Proportions Percentiles Expected Observed Expected Observed 0.990 0.990 1907.866 1902.838 0.980 0.982 1918.920 1919.168 0.950 0.944 1935.498 1929.891 0.900 0.900 1950.230 1949.416 0.800 0.792 1968.073 1966.434 0.700 0.704 1980.936 1981.272 0.500 0.486 2002.201 2001.320 0.300 0.318 2023.466 2024.623 0.200 0.210 2036.329 2039.384 0.100 0.100 2054.171 2054.155 0.050 0.040 2068.904 2065.736 0.020 0.016 2085.481 2083.032 0.010 0.006 2096.535 2093.005 Bayesian (BIC) Mean 2034.132 Std Dev 40.551 Number of successful computations 500 Proportions Percentiles Expected Observed Expected Observed 0.990 0.990 1939.798 1934.770 0.980 0.982 1950.852 1951.100 0.950 0.944 1967.429 1961.823 0.900 0.900 1982.162 1981.348 0.800 0.792 2000.004 1998.365 0.700 0.704 2012.867 2013.203 0.500 0.486 2034.132 2033.252 0.300 0.318 2055.398 2056.554 0.200 0.210 2068.260 2071.316 0.100 0.100 2086.103 2086.087 0.050 0.040 2100.835 2097.668 0.020 0.016 2117.413 2114.964 0.010 0.006 2128.467 2124.937 Sample-Size Adjusted BIC (n* = (n + 2) / 24) Mean 2008.748 Std Dev 40.551 Number of successful computations 500 Proportions Percentiles Expected Observed Expected Observed 0.990 0.990 1914.413 1909.386 0.980 0.982 1925.468 1925.715 0.950 0.944 1942.045 1936.439 0.900 0.900 1956.777 1955.963 0.800 0.792 1974.620 1972.981 0.700 0.704 1987.483 1987.819 0.500 0.486 2008.748 2007.868 0.300 0.318 2030.013 2031.170 0.200 0.210 2042.876 2045.931 0.100 0.100 2060.719 2060.702 0.050 0.040 2075.451 2072.284 0.020 0.016 2092.028 2089.579 0.010 0.006 2103.083 2099.552 MODEL RESULTS ESTIMATES S. E. M. S. E. 95% % Sig Population Average Std. Dev. Average Cover Coeff BETA1 ON X 0.200 0.2006 0.0716 0.0705 0.0051 0.954 0.806 Y ON X 0.400 0.4011 0.1784 0.1747 0.0318 0.944 0.622 M ON X 0.500 0.5015 0.0981 0.0997 0.0096 0.940 0.998 Intercepts Y 1.000 0.9984 0.1107 0.1110 0.0122 0.952 1.000 M 2.000 2.0032 0.0683 0.0707 0.0047 0.960 1.000 BETA1 0.500 0.5006 0.0493 0.0496 0.0024 0.962 1.000 Residual Variances Y 0.500 0.4968 0.0372 0.0348 0.0014 0.928 1.000 M 1.000 0.9933 0.0667 0.0699 0.0045 0.958 1.000 BETA1 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000 New/Additional Parameters TIE 0.350 0.3518 0.0748 0.0745 0.0056 0.930 0.998 PIE 0.250 0.2509 0.0544 0.0559 0.0029 0.946 0.998 DE 0.800 0.8027 0.0802 0.0765 0.0064 0.938 1.000 QUALITY OF NUMERICAL RESULTS Average Condition Number for the Information Matrix 0.123E-03 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU Y M X ________ ________ ________ 1 0 0 0 LAMBDA BETA1 Y M X ________ ________ ________ ________ Y 0 0 0 0 M 0 0 0 0 X 0 0 0 0 THETA Y M X ________ ________ ________ Y 0 M 0 0 X 0 0 0 ALPHA BETA1 Y M X ________ ________ ________ ________ 1 1 2 3 0 BETA BETA1 Y M X ________ ________ ________ ________ BETA1 0 0 0 4 Y 0 0 0 5 M 0 0 0 6 X 0 0 0 0 PSI BETA1 Y M X ________ ________ ________ ________ BETA1 0 Y 0 7 M 0 0 8 X 0 0 0 0 PARAMETER SPECIFICATION FOR THE ADDITIONAL PARAMETERS NEW/ADDITIONAL PARAMETERS TIE PIE DE ________ ________ ________ 1 9 10 11 STARTING VALUES NU Y M X ________ ________ ________ 1 0.000 0.000 0.000 LAMBDA BETA1 Y M X ________ ________ ________ ________ Y 0.000 1.000 0.000 0.000 M 0.000 0.000 1.000 0.000 X 0.000 0.000 0.000 1.000 THETA Y M X ________ ________ ________ Y 0.000 M 0.000 0.000 X 0.000 0.000 0.000 ALPHA BETA1 Y M X ________ ________ ________ ________ 1 0.500 1.000 2.000 0.000 BETA BETA1 Y M X ________ ________ ________ ________ BETA1 0.000 0.000 0.000 0.200 Y 0.000 0.000 0.000 0.400 M 0.000 0.000 0.000 0.500 X 0.000 0.000 0.000 0.000 PSI BETA1 Y M X ________ ________ ________ ________ BETA1 0.000 Y 0.000 0.500 M 0.000 0.000 1.000 X 0.000 0.000 0.000 0.500 STARTING VALUES FOR THE ADDITIONAL PARAMETERS NEW/ADDITIONAL PARAMETERS TIE PIE DE ________ ________ ________ 1 0.350 0.250 0.800 POPULATION VALUES NU Y M X ________ ________ ________ 1 0.000 0.000 0.000 LAMBDA BETA1 Y M X ________ ________ ________ ________ Y 0.000 1.000 0.000 0.000 M 0.000 0.000 1.000 0.000 X 0.000 0.000 0.000 1.000 THETA Y M X ________ ________ ________ Y 0.000 M 0.000 0.000 X 0.000 0.000 0.000 ALPHA BETA1 Y M X ________ ________ ________ ________ 1 0.500 1.000 2.000 0.000 BETA BETA1 Y M X ________ ________ ________ ________ BETA1 0.000 0.000 0.000 0.200 Y 0.000 0.000 0.000 0.400 M 0.000 0.000 0.000 0.500 X 0.000 0.000 0.000 0.000 PSI BETA1 Y M X ________ ________ ________ ________ BETA1 0.000 Y 0.000 0.500 M 0.000 0.000 1.000 X 0.000 0.000 0.000 1.000 SAVEDATA INFORMATION Order of variables Y M X Save file xmrep*.dat Save file format Free Save file record length 5000 Beginning Time: 12:16:58 Ending Time: 12:18:09 Elapsed Time: 00:01:11 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) 1998-2011 Muthen & Muthen