#Univariate LGCM - PCL: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE PCL1 PCL2 PCL3 PCL4 PCL5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | PCL1 PCL2 PCL3 PCL4 PCL5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous PCL1 PCL2 PCL3 PCL4 PCL5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 0.613 PCL2 0.446 0.776 PCL3 0.463 0.658 0.780 PCL4 0.398 0.583 0.613 0.683 PCL5 0.323 0.466 0.475 0.445 0.543 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 42.284 40.600 40.087 36.665 38.299 Covariances PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 375.022 PCL2 300.434 412.567 PCL3 280.202 349.695 422.317 PCL4 265.293 333.372 363.596 463.417 PCL5 251.639 293.319 307.585 335.521 390.562 Correlations PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1.000 PCL2 0.764 1.000 PCL3 0.704 0.838 1.000 PCL4 0.636 0.762 0.822 1.000 PCL5 0.658 0.731 0.757 0.789 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -9795.272 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 PCL1 42.465 -0.266 0.000 0.46% 24.000 40.000 43.000 437.000 366.528 -0.780 80.000 0.69% 50.000 61.000 PCL2 40.013 -0.163 0.000 1.08% 19.000 36.000 42.000 553.000 407.745 -0.933 80.000 1.27% 47.000 59.000 PCL3 40.027 -0.090 0.000 1.62% 20.000 35.000 41.000 556.000 417.310 -0.883 80.000 1.44% 47.000 58.000 PCL4 35.643 0.091 0.000 3.08% 15.000 28.000 36.000 487.000 449.720 -0.939 80.000 1.23% 43.000 56.000 PCL5 36.385 0.103 0.000 2.33% 18.000 30.000 36.000 387.000 382.366 -0.691 80.000 1.03% 42.000 54.000 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -9864.506 H0 Scaling Correction Factor 1.2464 for MLR Information Criteria Akaike (AIC) 19743.012 Bayesian (BIC) 19774.998 Sample-Size Adjusted BIC 19752.771 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 39.880 0.719 55.443 0.000 Intercepts PCL1 0.000 0.000 999.000 999.000 PCL2 0.000 0.000 999.000 999.000 PCL3 0.000 0.000 999.000 999.000 PCL4 0.000 0.000 999.000 999.000 PCL5 0.000 0.000 999.000 999.000 Variances P 323.447 15.292 21.151 0.000 Residual Variances PCL1 146.303 16.820 8.698 0.000 PCL2 78.482 8.127 9.657 0.000 PCL3 67.794 7.015 9.664 0.000 PCL4 124.163 12.811 9.692 0.000 PCL5 115.014 10.973 10.482 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.263E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ PCL1 0 PCL2 0 PCL3 0 PCL4 0 PCL5 0 THETA PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1 PCL2 0 2 PCL3 0 0 3 PCL4 0 0 0 4 PCL5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ PCL1 0.000 PCL2 0.000 PCL3 0.000 PCL4 0.000 PCL5 0.000 THETA PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 183.264 PCL2 0.000 203.872 PCL3 0.000 0.000 208.655 PCL4 0.000 0.000 0.000 224.860 PCL5 0.000 0.000 0.000 0.000 191.183 ALPHA P ________ 39.944 BETA P ________ P 0.000 PSI P ________ P 356.575 #Univariate LGCM - PCL: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE PCL1 PCL2 PCL3 PCL4 PCL5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | PCL1 PCL2 PCL3 PCL4 PCL5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous PCL1 PCL2 PCL3 PCL4 PCL5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 0.613 PCL2 0.446 0.776 PCL3 0.463 0.658 0.780 PCL4 0.398 0.583 0.613 0.683 PCL5 0.323 0.466 0.475 0.445 0.543 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 42.284 40.600 40.087 36.665 38.299 Covariances PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 375.022 PCL2 300.434 412.567 PCL3 280.202 349.695 422.317 PCL4 265.293 333.372 363.596 463.417 PCL5 251.639 293.319 307.585 335.521 390.562 Correlations PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1.000 PCL2 0.764 1.000 PCL3 0.704 0.838 1.000 PCL4 0.636 0.762 0.822 1.000 PCL5 0.658 0.731 0.757 0.789 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -9795.272 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 PCL1 42.465 -0.266 0.000 0.46% 24.000 40.000 43.000 437.000 366.528 -0.780 80.000 0.69% 50.000 61.000 PCL2 40.013 -0.163 0.000 1.08% 19.000 36.000 42.000 553.000 407.745 -0.933 80.000 1.27% 47.000 59.000 PCL3 40.027 -0.090 0.000 1.62% 20.000 35.000 41.000 556.000 417.310 -0.883 80.000 1.44% 47.000 58.000 PCL4 35.643 0.091 0.000 3.08% 15.000 28.000 36.000 487.000 449.720 -0.939 80.000 1.23% 43.000 56.000 PCL5 36.385 0.103 0.000 2.33% 18.000 30.000 36.000 387.000 382.366 -0.691 80.000 1.03% 42.000 54.000 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -9842.255 H0 Scaling Correction Factor 1.1424 for MLR Information Criteria Akaike (AIC) 19704.511 Bayesian (BIC) 19750.205 Sample-Size Adjusted BIC 19718.453 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -22.680 6.152 -3.687 0.000 Means P 45.132 1.327 34.019 0.000 PS -0.544 0.118 -4.617 0.000 Intercepts PCL1 0.000 0.000 999.000 999.000 PCL2 0.000 0.000 999.000 999.000 PCL3 0.000 0.000 999.000 999.000 PCL4 0.000 0.000 999.000 999.000 PCL5 0.000 0.000 999.000 999.000 Variances P 535.046 68.398 7.823 0.000 PS 2.376 0.598 3.971 0.000 Residual Variances PCL1 112.412 16.809 6.687 0.000 PCL2 71.692 7.899 9.076 0.000 PCL3 72.105 7.071 10.197 0.000 PCL4 114.269 11.776 9.704 0.000 PCL5 79.265 12.981 6.106 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.123E-02 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ PCL1 0 0 PCL2 0 0 PCL3 0 0 PCL4 0 0 PCL5 0 0 THETA PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1 PCL2 0 2 PCL3 0 0 3 PCL4 0 0 0 4 PCL5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ PCL1 0.000 0.000 PCL2 0.000 0.000 PCL3 0.000 0.000 PCL4 0.000 0.000 PCL5 0.000 0.000 THETA PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 183.264 PCL2 0.000 203.872 PCL3 0.000 0.000 208.655 PCL4 0.000 0.000 0.000 224.860 PCL5 0.000 0.000 0.000 0.000 191.183 ALPHA P PS ________ ________ 43.270 -0.266 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 1037.540 PS 0.000 11.905 #Univariate LGCM - PCL: Male quadratic INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE PCL1 PCL2 PCL3 PCL4 PCL5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | PCL1 PCL2 PCL3 PCL4 PCL5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous PCL1 PCL2 PCL3 PCL4 PCL5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 0.613 PCL2 0.446 0.776 PCL3 0.463 0.658 0.780 PCL4 0.398 0.583 0.613 0.683 PCL5 0.323 0.466 0.475 0.445 0.543 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 42.284 40.600 40.087 36.665 38.299 Covariances PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 375.022 PCL2 300.434 412.567 PCL3 280.202 349.695 422.317 PCL4 265.293 333.372 363.596 463.417 PCL5 251.639 293.319 307.585 335.521 390.562 Correlations PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1.000 PCL2 0.764 1.000 PCL3 0.704 0.838 1.000 PCL4 0.636 0.762 0.822 1.000 PCL5 0.658 0.731 0.757 0.789 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -9795.272 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 PCL1 42.465 -0.266 0.000 0.46% 24.000 40.000 43.000 437.000 366.528 -0.780 80.000 0.69% 50.000 61.000 PCL2 40.013 -0.163 0.000 1.08% 19.000 36.000 42.000 553.000 407.745 -0.933 80.000 1.27% 47.000 59.000 PCL3 40.027 -0.090 0.000 1.62% 20.000 35.000 41.000 556.000 417.310 -0.883 80.000 1.44% 47.000 58.000 PCL4 35.643 0.091 0.000 3.08% 15.000 28.000 36.000 487.000 449.720 -0.939 80.000 1.23% 43.000 56.000 PCL5 36.385 0.103 0.000 2.33% 18.000 30.000 36.000 387.000 382.366 -0.691 80.000 1.03% 42.000 54.000 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -9834.496 H0 Scaling Correction Factor 0.9585 for MLR Information Criteria Akaike (AIC) 19696.992 Bayesian (BIC) 19760.965 Sample-Size Adjusted BIC 19716.511 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -37.046 21.506 -1.723 0.085 PQ WITH P 0.244 0.729 0.335 0.738 PS -0.420 0.144 -2.913 0.004 Means P 48.668 2.973 16.372 0.000 PS -1.290 0.579 -2.230 0.026 PQ 0.037 0.027 1.362 0.173 Intercepts PCL1 0.000 0.000 999.000 999.000 PCL2 0.000 0.000 999.000 999.000 PCL3 0.000 0.000 999.000 999.000 PCL4 0.000 0.000 999.000 999.000 PCL5 0.000 0.000 999.000 999.000 Variances P 473.660 125.746 3.767 0.000 PS 12.006 4.022 2.985 0.003 PQ 0.020 0.005 3.576 0.000 Residual Variances PCL1 109.451 16.519 6.626 0.000 PCL2 69.939 7.994 8.749 0.000 PCL3 69.827 7.049 9.906 0.000 PCL4 109.297 11.454 9.542 0.000 PCL5 68.827 12.062 5.706 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.233E-07 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ PCL1 0 0 0 PCL2 0 0 0 PCL3 0 0 0 PCL4 0 0 0 PCL5 0 0 0 THETA PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1 PCL2 0 2 PCL3 0 0 3 PCL4 0 0 0 4 PCL5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ PCL1 0.000 0.000 0.000 PCL2 0.000 0.000 0.000 PCL3 0.000 0.000 0.000 PCL4 0.000 0.000 0.000 PCL5 0.000 0.000 0.000 THETA PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 183.264 PCL2 0.000 203.872 PCL3 0.000 0.000 208.655 PCL4 0.000 0.000 0.000 224.860 PCL5 0.000 0.000 0.000 0.000 191.183 ALPHA P PS PQ ________ ________ ________ 37.784 1.378 -0.107 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 4440.530 PS 0.000 320.600 PQ 0.000 0.000 2.436 #Univariate LGCM - IPF Total: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | Tot1 Tot2 Tot3 Tot4 Tot5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous TOT1 TOT2 TOT3 TOT4 TOT5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 21 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 0.990 TOT2 0.833 0.840 TOT3 0.823 0.764 0.830 TOT4 0.743 0.694 0.711 0.752 TOT5 0.595 0.547 0.551 0.540 0.600 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 42.214 39.609 39.825 38.751 38.158 Covariances TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 259.316 TOT2 172.368 239.153 TOT3 183.442 203.036 272.565 TOT4 165.349 186.609 209.548 266.015 TOT5 170.384 178.053 204.995 206.693 270.290 Correlations TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1.000 TOT2 0.692 1.000 TOT3 0.690 0.795 1.000 TOT4 0.630 0.740 0.778 1.000 TOT5 0.644 0.700 0.755 0.771 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11001.185 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 TOT1 42.190 0.144 4.309 0.14% 27.477 37.136 41.572 706.000 259.849 -0.455 93.528 0.14% 45.784 56.944 TOT2 39.422 0.219 2.639 0.17% 25.680 35.024 39.108 599.000 240.497 -0.062 89.509 0.17% 42.714 52.041 TOT3 39.926 0.118 0.000 0.17% 24.619 35.714 39.893 592.000 273.639 -0.216 95.833 0.17% 43.902 54.266 TOT4 38.492 0.191 0.694 0.19% 23.645 34.011 38.499 536.000 264.218 -0.235 87.798 0.19% 43.262 51.792 TOT5 37.117 0.247 0.595 0.23% 21.923 31.879 37.699 428.000 259.337 -0.291 92.496 0.23% 41.543 50.135 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -11054.729 H0 Scaling Correction Factor 1.1921 for MLR Information Criteria Akaike (AIC) 22123.458 Bayesian (BIC) 22155.445 Sample-Size Adjusted BIC 22133.218 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 39.838 0.547 72.827 0.000 Intercepts TOT1 0.000 0.000 999.000 999.000 TOT2 0.000 0.000 999.000 999.000 TOT3 0.000 0.000 999.000 999.000 TOT4 0.000 0.000 999.000 999.000 TOT5 0.000 0.000 999.000 999.000 Variances P 189.954 10.869 17.476 0.000 Residual Variances TOT1 113.381 8.086 14.021 0.000 TOT2 55.328 5.176 10.689 0.000 TOT3 55.498 4.934 11.248 0.000 TOT4 70.508 6.592 10.696 0.000 TOT5 81.403 7.229 11.261 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.232E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ TOT1 0 TOT2 0 TOT3 0 TOT4 0 TOT5 0 THETA TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1 TOT2 0 2 TOT3 0 0 3 TOT4 0 0 0 4 TOT5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ TOT1 0.000 TOT2 0.000 TOT3 0.000 TOT4 0.000 TOT5 0.000 THETA TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 129.925 TOT2 0.000 120.249 TOT3 0.000 0.000 136.820 TOT4 0.000 0.000 0.000 132.109 TOT5 0.000 0.000 0.000 0.000 129.668 ALPHA P ________ 40.082 BETA P ________ P 0.000 PSI P ________ P 209.693 #Univariate LGCM - IPF Total: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | Tot1 Tot2 Tot3 Tot4 Tot5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous TOT1 TOT2 TOT3 TOT4 TOT5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 21 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 0.990 TOT2 0.833 0.840 TOT3 0.823 0.764 0.830 TOT4 0.743 0.694 0.711 0.752 TOT5 0.595 0.547 0.551 0.540 0.600 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 42.214 39.609 39.825 38.751 38.158 Covariances TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 259.316 TOT2 172.368 239.153 TOT3 183.442 203.036 272.565 TOT4 165.349 186.609 209.548 266.015 TOT5 170.384 178.053 204.995 206.693 270.290 Correlations TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1.000 TOT2 0.692 1.000 TOT3 0.690 0.795 1.000 TOT4 0.630 0.740 0.778 1.000 TOT5 0.644 0.700 0.755 0.771 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11001.185 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 TOT1 42.190 0.144 4.309 0.14% 27.477 37.136 41.572 706.000 259.849 -0.455 93.528 0.14% 45.784 56.944 TOT2 39.422 0.219 2.639 0.17% 25.680 35.024 39.108 599.000 240.497 -0.062 89.509 0.17% 42.714 52.041 TOT3 39.926 0.118 0.000 0.17% 24.619 35.714 39.893 592.000 273.639 -0.216 95.833 0.17% 43.902 54.266 TOT4 38.492 0.191 0.694 0.19% 23.645 34.011 38.499 536.000 264.218 -0.235 87.798 0.19% 43.262 51.792 TOT5 37.117 0.247 0.595 0.23% 21.923 31.879 37.699 428.000 259.337 -0.291 92.496 0.23% 41.543 50.135 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -11024.562 H0 Scaling Correction Factor 1.1367 for MLR Information Criteria Akaike (AIC) 22069.125 Bayesian (BIC) 22114.820 Sample-Size Adjusted BIC 22083.067 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -5.627 2.822 -1.994 0.046 Means P 44.744 0.899 49.798 0.000 PS -0.514 0.081 -6.340 0.000 Intercepts TOT1 0.000 0.000 999.000 999.000 TOT2 0.000 0.000 999.000 999.000 TOT3 0.000 0.000 999.000 999.000 TOT4 0.000 0.000 999.000 999.000 TOT5 0.000 0.000 999.000 999.000 Variances P 218.126 30.456 7.162 0.000 PS 0.866 0.298 2.909 0.004 Residual Variances TOT1 94.518 8.768 10.780 0.000 TOT2 56.400 5.222 10.800 0.000 TOT3 56.746 4.933 11.504 0.000 TOT4 65.778 6.596 9.973 0.000 TOT5 63.085 7.801 8.087 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.369E-03 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ TOT1 0 0 TOT2 0 0 TOT3 0 0 TOT4 0 0 TOT5 0 0 THETA TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1 TOT2 0 2 TOT3 0 0 3 TOT4 0 0 0 4 TOT5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ TOT1 0.000 0.000 TOT2 0.000 0.000 TOT3 0.000 0.000 TOT4 0.000 0.000 TOT5 0.000 0.000 THETA TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 129.925 TOT2 0.000 120.249 TOT3 0.000 0.000 136.820 TOT4 0.000 0.000 0.000 132.109 TOT5 0.000 0.000 0.000 0.000 129.668 ALPHA P PS ________ ________ 43.859 -0.323 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 550.290 PS 0.000 6.942 #Univariate LGCM - IPF Total: Male quadratic INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | Tot1 Tot2 Tot3 Tot4 Tot5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous TOT1 TOT2 TOT3 TOT4 TOT5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 21 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 0.990 TOT2 0.833 0.840 TOT3 0.823 0.764 0.830 TOT4 0.743 0.694 0.711 0.752 TOT5 0.595 0.547 0.551 0.540 0.600 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 42.214 39.609 39.825 38.751 38.158 Covariances TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 259.316 TOT2 172.368 239.153 TOT3 183.442 203.036 272.565 TOT4 165.349 186.609 209.548 266.015 TOT5 170.384 178.053 204.995 206.693 270.290 Correlations TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1.000 TOT2 0.692 1.000 TOT3 0.690 0.795 1.000 TOT4 0.630 0.740 0.778 1.000 TOT5 0.644 0.700 0.755 0.771 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11001.185 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 TOT1 42.190 0.144 4.309 0.14% 27.477 37.136 41.572 706.000 259.849 -0.455 93.528 0.14% 45.784 56.944 TOT2 39.422 0.219 2.639 0.17% 25.680 35.024 39.108 599.000 240.497 -0.062 89.509 0.17% 42.714 52.041 TOT3 39.926 0.118 0.000 0.17% 24.619 35.714 39.893 592.000 273.639 -0.216 95.833 0.17% 43.902 54.266 TOT4 38.492 0.191 0.694 0.19% 23.645 34.011 38.499 536.000 264.218 -0.235 87.798 0.19% 43.262 51.792 TOT5 37.117 0.247 0.595 0.23% 21.923 31.879 37.699 428.000 259.337 -0.291 92.496 0.23% 41.543 50.135 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -11019.176 H0 Scaling Correction Factor 1.0176 for MLR Information Criteria Akaike (AIC) 22066.352 Bayesian (BIC) 22130.325 Sample-Size Adjusted BIC 22085.871 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -18.163 14.678 -1.237 0.216 PQ WITH P 0.484 0.644 0.751 0.452 PS -0.263 0.145 -1.821 0.069 Means P 45.723 1.776 25.752 0.000 PS -0.726 0.360 -2.016 0.044 PQ 0.011 0.018 0.609 0.542 Intercepts TOT1 0.000 0.000 999.000 999.000 TOT2 0.000 0.000 999.000 999.000 TOT3 0.000 0.000 999.000 999.000 TOT4 0.000 0.000 999.000 999.000 TOT5 0.000 0.000 999.000 999.000 Variances P 224.754 71.014 3.165 0.002 PS 6.434 3.257 1.976 0.048 PQ 0.013 0.007 1.960 0.050 Residual Variances TOT1 90.026 8.774 10.261 0.000 TOT2 55.682 5.169 10.771 0.000 TOT3 54.581 4.901 11.136 0.000 TOT4 65.643 6.562 10.003 0.000 TOT5 58.596 7.458 7.857 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.184E-07 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ TOT1 0 0 0 TOT2 0 0 0 TOT3 0 0 0 TOT4 0 0 0 TOT5 0 0 0 THETA TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1 TOT2 0 2 TOT3 0 0 3 TOT4 0 0 0 4 TOT5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ TOT1 0.000 0.000 0.000 TOT2 0.000 0.000 0.000 TOT3 0.000 0.000 0.000 TOT4 0.000 0.000 0.000 TOT5 0.000 0.000 0.000 THETA TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 129.925 TOT2 0.000 120.249 TOT3 0.000 0.000 136.820 TOT4 0.000 0.000 0.000 132.109 TOT5 0.000 0.000 0.000 0.000 129.668 ALPHA P PS PQ ________ ________ ________ 47.099 -2.677 0.251 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 1876.924 PS 0.000 147.795 PQ 0.000 0.000 1.175 #Univariate LGCM - IPF Family: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Fam1 Fam2 Fam3 Fam4 Fam5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | Fam1 Fam2 Fam3 Fam4 Fam5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 695 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous FAM1 FAM2 FAM3 FAM4 FAM5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 30 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 0.917 FAM2 0.722 0.778 FAM3 0.678 0.635 0.737 FAM4 0.626 0.587 0.586 0.681 FAM5 0.508 0.466 0.456 0.460 0.555 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 50.157 48.183 48.167 45.989 46.440 Covariances FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 448.862 FAM2 270.286 489.900 FAM3 274.590 343.915 534.396 FAM4 238.371 289.620 313.745 503.316 FAM5 250.451 298.588 334.852 314.239 500.806 Correlations FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1.000 FAM2 0.576 1.000 FAM3 0.561 0.672 1.000 FAM4 0.502 0.583 0.605 1.000 FAM5 0.528 0.603 0.647 0.626 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10987.719 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 FAM1 49.960 -0.065 0.000 0.78% 30.952 45.238 50.000 637.000 448.409 -0.521 100.000 0.16% 54.762 69.048 FAM2 47.824 -0.055 0.000 2.40% 28.571 41.667 47.619 541.000 493.899 -0.524 100.000 0.18% 52.778 66.667 FAM3 47.304 -0.024 0.000 1.95% 28.571 40.476 47.619 512.000 521.036 -0.649 100.000 0.20% 52.381 69.048 FAM4 44.745 0.053 0.000 1.90% 23.810 38.095 45.238 473.000 492.268 -0.644 97.619 0.21% 52.381 64.286 FAM5 44.539 0.076 0.000 2.33% 23.810 38.095 42.857 386.000 489.315 -0.591 100.000 0.26% 50.000 64.286 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -11014.176 H0 Scaling Correction Factor 1.0064 for MLR Information Criteria Akaike (AIC) 22042.351 Bayesian (BIC) 22074.159 Sample-Size Adjusted BIC 22051.932 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 48.062 0.721 66.655 0.000 Intercepts FAM1 0.000 0.000 999.000 999.000 FAM2 0.000 0.000 999.000 999.000 FAM3 0.000 0.000 999.000 999.000 FAM4 0.000 0.000 999.000 999.000 FAM5 0.000 0.000 999.000 999.000 Variances P 291.151 17.472 16.664 0.000 Residual Variances FAM1 227.911 18.134 12.568 0.000 FAM2 177.989 14.489 12.284 0.000 FAM3 192.166 14.746 13.032 0.000 FAM4 225.661 18.483 12.209 0.000 FAM5 200.642 19.103 10.503 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.237E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ FAM1 0 FAM2 0 FAM3 0 FAM4 0 FAM5 0 THETA FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1 FAM2 0 2 FAM3 0 0 3 FAM4 0 0 0 4 FAM5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ FAM1 0.000 FAM2 0.000 FAM3 0.000 FAM4 0.000 FAM5 0.000 THETA FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 224.204 FAM2 0.000 246.949 FAM3 0.000 0.000 260.518 FAM4 0.000 0.000 0.000 246.134 FAM5 0.000 0.000 0.000 0.000 244.658 ALPHA P ________ 48.380 BETA P ________ P 0.000 PSI P ________ P 358.031 #Univariate LGCM - IPF Family: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Fam1 Fam2 Fam3 Fam4 Fam5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | Fam1 Fam2 Fam3 Fam4 Fam5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 695 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous FAM1 FAM2 FAM3 FAM4 FAM5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 30 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 0.917 FAM2 0.722 0.778 FAM3 0.678 0.635 0.737 FAM4 0.626 0.587 0.586 0.681 FAM5 0.508 0.466 0.456 0.460 0.555 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 50.157 48.183 48.167 45.989 46.440 Covariances FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 448.862 FAM2 270.286 489.900 FAM3 274.590 343.915 534.396 FAM4 238.371 289.620 313.745 503.316 FAM5 250.451 298.588 334.852 314.239 500.806 Correlations FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1.000 FAM2 0.576 1.000 FAM3 0.561 0.672 1.000 FAM4 0.502 0.583 0.605 1.000 FAM5 0.528 0.603 0.647 0.626 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10987.719 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 FAM1 49.960 -0.065 0.000 0.78% 30.952 45.238 50.000 637.000 448.409 -0.521 100.000 0.16% 54.762 69.048 FAM2 47.824 -0.055 0.000 2.40% 28.571 41.667 47.619 541.000 493.899 -0.524 100.000 0.18% 52.778 66.667 FAM3 47.304 -0.024 0.000 1.95% 28.571 40.476 47.619 512.000 521.036 -0.649 100.000 0.20% 52.381 69.048 FAM4 44.745 0.053 0.000 1.90% 23.810 38.095 45.238 473.000 492.268 -0.644 97.619 0.21% 52.381 64.286 FAM5 44.539 0.076 0.000 2.33% 23.810 38.095 42.857 386.000 489.315 -0.591 100.000 0.26% 50.000 64.286 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -11002.431 H0 Scaling Correction Factor 0.9805 for MLR Information Criteria Akaike (AIC) 22024.862 Bayesian (BIC) 22070.301 Sample-Size Adjusted BIC 22038.549 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -10.681 6.421 -1.663 0.096 Means P 52.750 1.356 38.898 0.000 PS -0.493 0.129 -3.836 0.000 Intercepts FAM1 0.000 0.000 999.000 999.000 FAM2 0.000 0.000 999.000 999.000 FAM3 0.000 0.000 999.000 999.000 FAM4 0.000 0.000 999.000 999.000 FAM5 0.000 0.000 999.000 999.000 Variances P 356.523 68.817 5.181 0.000 PS 1.521 0.664 2.290 0.022 Residual Variances FAM1 202.274 18.758 10.783 0.000 FAM2 181.222 14.663 12.359 0.000 FAM3 193.917 14.723 13.171 0.000 FAM4 218.391 18.634 11.720 0.000 FAM5 163.327 22.575 7.235 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.231E-03 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ FAM1 0 0 FAM2 0 0 FAM3 0 0 FAM4 0 0 FAM5 0 0 THETA FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1 FAM2 0 2 FAM3 0 0 3 FAM4 0 0 0 4 FAM5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ FAM1 0.000 0.000 FAM2 0.000 0.000 FAM3 0.000 0.000 FAM4 0.000 0.000 FAM5 0.000 0.000 THETA FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 224.204 FAM2 0.000 246.949 FAM3 0.000 0.000 260.518 FAM4 0.000 0.000 0.000 246.134 FAM5 0.000 0.000 0.000 0.000 244.658 ALPHA P PS ________ ________ 50.908 -0.241 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 1172.339 PS 0.000 14.101 #Univariate LGCM - IPF Family: Male quadratic INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Fam1 Fam2 Fam3 Fam4 Fam5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | Fam1 Fam2 Fam3 Fam4 Fam5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 695 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous FAM1 FAM2 FAM3 FAM4 FAM5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 30 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 0.917 FAM2 0.722 0.778 FAM3 0.678 0.635 0.737 FAM4 0.626 0.587 0.586 0.681 FAM5 0.508 0.466 0.456 0.460 0.555 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 50.157 48.183 48.167 45.989 46.440 Covariances FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 448.862 FAM2 270.286 489.900 FAM3 274.590 343.915 534.396 FAM4 238.371 289.620 313.745 503.316 FAM5 250.451 298.588 334.852 314.239 500.806 Correlations FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1.000 FAM2 0.576 1.000 FAM3 0.561 0.672 1.000 FAM4 0.502 0.583 0.605 1.000 FAM5 0.528 0.603 0.647 0.626 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10987.719 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 FAM1 49.960 -0.065 0.000 0.78% 30.952 45.238 50.000 637.000 448.409 -0.521 100.000 0.16% 54.762 69.048 FAM2 47.824 -0.055 0.000 2.40% 28.571 41.667 47.619 541.000 493.899 -0.524 100.000 0.18% 52.778 66.667 FAM3 47.304 -0.024 0.000 1.95% 28.571 40.476 47.619 512.000 521.036 -0.649 100.000 0.20% 52.381 69.048 FAM4 44.745 0.053 0.000 1.90% 23.810 38.095 45.238 473.000 492.268 -0.644 97.619 0.21% 52.381 64.286 FAM5 44.539 0.076 0.000 2.33% 23.810 38.095 42.857 386.000 489.315 -0.591 100.000 0.26% 50.000 64.286 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -10998.377 H0 Scaling Correction Factor 0.9097 for MLR Information Criteria Akaike (AIC) 22024.754 Bayesian (BIC) 22088.369 Sample-Size Adjusted BIC 22043.916 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -16.641 34.487 -0.483 0.629 PQ WITH P 0.165 1.490 0.111 0.912 PS -0.366 0.338 -1.083 0.279 Means P 50.085 2.711 18.472 0.000 PS 0.113 0.569 0.199 0.843 PQ -0.031 0.029 -1.075 0.282 Intercepts FAM1 0.000 0.000 999.000 999.000 FAM2 0.000 0.000 999.000 999.000 FAM3 0.000 0.000 999.000 999.000 FAM4 0.000 0.000 999.000 999.000 FAM5 0.000 0.000 999.000 999.000 Variances P 292.355 160.833 1.818 0.069 PS 8.552 7.725 1.107 0.268 PQ 0.020 0.015 1.348 0.178 Residual Variances FAM1 196.974 19.427 10.139 0.000 FAM2 175.625 14.637 11.999 0.000 FAM3 189.735 14.836 12.789 0.000 FAM4 218.942 19.178 11.416 0.000 FAM5 150.829 21.588 6.987 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.173E-07 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ FAM1 0 0 0 FAM2 0 0 0 FAM3 0 0 0 FAM4 0 0 0 FAM5 0 0 0 THETA FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1 FAM2 0 2 FAM3 0 0 3 FAM4 0 0 0 4 FAM5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ FAM1 0.000 0.000 0.000 FAM2 0.000 0.000 0.000 FAM3 0.000 0.000 0.000 FAM4 0.000 0.000 0.000 FAM5 0.000 0.000 0.000 THETA FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 224.204 FAM2 0.000 246.949 FAM3 0.000 0.000 260.518 FAM4 0.000 0.000 0.000 246.134 FAM5 0.000 0.000 0.000 0.000 244.658 ALPHA P PS PQ ________ ________ ________ 41.339 2.905 -0.349 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 5313.003 PS 0.000 501.081 PQ 0.000 0.000 4.181 #Univariate LGCM - IPF Friend: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 669 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous FND1 FND2 FND3 FND4 FND5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 0.858 FND2 0.631 0.725 FND3 0.599 0.571 0.685 FND4 0.531 0.508 0.511 0.604 FND5 0.435 0.410 0.401 0.384 0.505 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 45.845 42.158 42.983 41.051 39.612 Covariances FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 403.949 FND2 234.387 386.234 FND3 255.124 296.966 436.822 FND4 219.837 257.730 313.392 393.450 FND5 209.678 240.791 292.643 244.502 416.678 Correlations FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1.000 FND2 0.593 1.000 FND3 0.607 0.723 1.000 FND4 0.551 0.661 0.756 1.000 FND5 0.511 0.600 0.686 0.604 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -9444.626 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 FND1 44.972 -0.079 0.000 0.87% 25.000 41.667 45.833 574.000 402.064 -0.478 95.833 0.17% 50.000 62.500 FND2 40.985 0.035 0.000 2.27% 22.917 35.417 41.667 485.000 382.215 -0.384 97.917 0.21% 47.917 58.333 FND3 41.179 0.052 0.000 2.40% 20.833 35.417 41.667 458.000 423.450 -0.506 100.000 0.22% 47.917 60.417 FND4 38.565 0.116 0.000 1.98% 20.833 33.333 39.583 404.000 374.501 -0.529 95.833 0.25% 43.750 56.250 FND5 37.341 0.092 0.000 3.85% 18.750 31.250 37.500 338.000 398.869 -0.461 97.917 0.30% 43.750 54.167 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -9489.072 H0 Scaling Correction Factor 1.1409 for MLR Information Criteria Akaike (AIC) 18992.145 Bayesian (BIC) 19023.685 Sample-Size Adjusted BIC 19001.460 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 42.633 0.707 60.277 0.000 Intercepts FND1 0.000 0.000 999.000 999.000 FND2 0.000 0.000 999.000 999.000 FND3 0.000 0.000 999.000 999.000 FND4 0.000 0.000 999.000 999.000 FND5 0.000 0.000 999.000 999.000 Variances P 264.713 15.152 17.471 0.000 Residual Variances FND1 216.911 19.363 11.202 0.000 FND2 126.106 11.631 10.842 0.000 FND3 109.123 11.652 9.365 0.000 FND4 128.278 14.438 8.884 0.000 FND5 188.545 18.141 10.394 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.255E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ FND1 0 FND2 0 FND3 0 FND4 0 FND5 0 THETA FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1 FND2 0 2 FND3 0 0 3 FND4 0 0 0 4 FND5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ FND1 0.000 FND2 0.000 FND3 0.000 FND4 0.000 FND5 0.000 THETA FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 201.032 FND2 0.000 191.107 FND3 0.000 0.000 211.725 FND4 0.000 0.000 0.000 187.251 FND5 0.000 0.000 0.000 0.000 199.434 ALPHA P ________ 43.378 BETA P ________ P 0.000 PSI P ________ P 322.389 #Univariate LGCM - IPF Friend: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 669 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous FND1 FND2 FND3 FND4 FND5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 0.858 FND2 0.631 0.725 FND3 0.599 0.571 0.685 FND4 0.531 0.508 0.511 0.604 FND5 0.435 0.410 0.401 0.384 0.505 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 45.845 42.158 42.983 41.051 39.612 Covariances FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 403.949 FND2 234.387 386.234 FND3 255.124 296.966 436.822 FND4 219.837 257.730 313.392 393.450 FND5 209.678 240.791 292.643 244.502 416.678 Correlations FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1.000 FND2 0.593 1.000 FND3 0.607 0.723 1.000 FND4 0.551 0.661 0.756 1.000 FND5 0.511 0.600 0.686 0.604 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -9444.626 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 FND1 44.972 -0.079 0.000 0.87% 25.000 41.667 45.833 574.000 402.064 -0.478 95.833 0.17% 50.000 62.500 FND2 40.985 0.035 0.000 2.27% 22.917 35.417 41.667 485.000 382.215 -0.384 97.917 0.21% 47.917 58.333 FND3 41.179 0.052 0.000 2.40% 20.833 35.417 41.667 458.000 423.450 -0.506 100.000 0.22% 47.917 60.417 FND4 38.565 0.116 0.000 1.98% 20.833 33.333 39.583 404.000 374.501 -0.529 95.833 0.25% 43.750 56.250 FND5 37.341 0.092 0.000 3.85% 18.750 31.250 37.500 338.000 398.869 -0.461 97.917 0.30% 43.750 54.167 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -9465.757 H0 Scaling Correction Factor 1.0914 for MLR Information Criteria Akaike (AIC) 18951.514 Bayesian (BIC) 18996.572 Sample-Size Adjusted BIC 18964.821 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -8.712 6.624 -1.315 0.188 Means P 49.920 1.345 37.128 0.000 PS -0.775 0.127 -6.094 0.000 Intercepts FND1 0.000 0.000 999.000 999.000 FND2 0.000 0.000 999.000 999.000 FND3 0.000 0.000 999.000 999.000 FND4 0.000 0.000 999.000 999.000 FND5 0.000 0.000 999.000 999.000 Variances P 314.505 68.104 4.618 0.000 PS 1.237 0.684 1.807 0.071 Residual Variances FND1 185.389 21.325 8.694 0.000 FND2 128.246 11.504 11.148 0.000 FND3 110.684 11.562 9.573 0.000 FND4 122.472 14.566 8.408 0.000 FND5 160.600 19.857 8.088 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.228E-03 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ FND1 0 0 FND2 0 0 FND3 0 0 FND4 0 0 FND5 0 0 THETA FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1 FND2 0 2 FND3 0 0 3 FND4 0 0 0 4 FND5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ FND1 0.000 0.000 FND2 0.000 0.000 FND3 0.000 0.000 FND4 0.000 0.000 FND5 0.000 0.000 THETA FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 201.032 FND2 0.000 191.107 FND3 0.000 0.000 211.725 FND4 0.000 0.000 0.000 187.251 FND5 0.000 0.000 0.000 0.000 199.434 ALPHA P PS ________ ________ 49.710 -0.615 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 1018.363 PS 0.000 13.547 #Univariate LGCM - IPF Friend: Male quadratic INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 669 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous FND1 FND2 FND3 FND4 FND5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 0.858 FND2 0.631 0.725 FND3 0.599 0.571 0.685 FND4 0.531 0.508 0.511 0.604 FND5 0.435 0.410 0.401 0.384 0.505 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 45.845 42.158 42.983 41.051 39.612 Covariances FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 403.949 FND2 234.387 386.234 FND3 255.124 296.966 436.822 FND4 219.837 257.730 313.392 393.450 FND5 209.678 240.791 292.643 244.502 416.678 Correlations FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1.000 FND2 0.593 1.000 FND3 0.607 0.723 1.000 FND4 0.551 0.661 0.756 1.000 FND5 0.511 0.600 0.686 0.604 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -9444.626 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 FND1 44.972 -0.079 0.000 0.87% 25.000 41.667 45.833 574.000 402.064 -0.478 95.833 0.17% 50.000 62.500 FND2 40.985 0.035 0.000 2.27% 22.917 35.417 41.667 485.000 382.215 -0.384 97.917 0.21% 47.917 58.333 FND3 41.179 0.052 0.000 2.40% 20.833 35.417 41.667 458.000 423.450 -0.506 100.000 0.22% 47.917 60.417 FND4 38.565 0.116 0.000 1.98% 20.833 33.333 39.583 404.000 374.501 -0.529 95.833 0.25% 43.750 56.250 FND5 37.341 0.092 0.000 3.85% 18.750 31.250 37.500 338.000 398.869 -0.461 97.917 0.30% 43.750 54.167 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -9463.127 H0 Scaling Correction Factor 0.9325 for MLR Information Criteria Akaike (AIC) 18954.253 Bayesian (BIC) 19017.334 Sample-Size Adjusted BIC 18972.883 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -32.366 26.375 -1.227 0.220 PQ WITH P 0.756 1.013 0.746 0.456 PS -0.363 0.228 -1.594 0.111 Means P 52.439 2.599 20.176 0.000 PS -1.347 0.539 -2.498 0.012 PQ 0.030 0.028 1.095 0.274 Intercepts FND1 0.000 0.000 999.000 999.000 FND2 0.000 0.000 999.000 999.000 FND3 0.000 0.000 999.000 999.000 FND4 0.000 0.000 999.000 999.000 FND5 0.000 0.000 999.000 999.000 Variances P 376.236 136.143 2.764 0.006 PS 9.585 5.649 1.697 0.090 PQ 0.017 0.009 1.781 0.075 Residual Variances FND1 175.440 21.477 8.169 0.000 FND2 127.228 11.659 10.912 0.000 FND3 106.948 11.641 9.188 0.000 FND4 121.567 14.552 8.354 0.000 FND5 154.743 18.914 8.182 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.271E-07 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ FND1 0 0 0 FND2 0 0 0 FND3 0 0 0 FND4 0 0 0 FND5 0 0 0 THETA FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1 FND2 0 2 FND3 0 0 3 FND4 0 0 0 4 FND5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ FND1 0.000 0.000 0.000 FND2 0.000 0.000 0.000 FND3 0.000 0.000 0.000 FND4 0.000 0.000 0.000 FND5 0.000 0.000 0.000 THETA FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 201.032 FND2 0.000 191.107 FND3 0.000 0.000 211.725 FND4 0.000 0.000 0.000 187.251 FND5 0.000 0.000 0.000 0.000 199.434 ALPHA P PS PQ ________ ________ ________ 51.819 -3.330 0.272 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 3435.341 PS 0.000 277.932 PQ 0.000 0.000 2.017 #Univariate LGCM - IPF Romantic Relationships: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Rom1 Rom2 Rom3 Rom4 Rom5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | Rom1 Rom2 Rom3 Rom4 Rom5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 630 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous ROM1 ROM2 ROM3 ROM4 ROM5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 0.752 ROM2 0.541 0.679 ROM3 0.549 0.551 0.697 ROM4 0.495 0.498 0.543 0.641 ROM5 0.403 0.394 0.413 0.403 0.530 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 40.594 36.749 37.950 36.248 36.300 Covariances ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 335.585 ROM2 190.453 322.111 ROM3 190.343 223.867 345.007 ROM4 171.010 211.897 253.812 350.451 ROM5 182.203 176.607 220.521 222.326 357.831 Correlations ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1.000 ROM2 0.579 1.000 ROM3 0.559 0.672 1.000 ROM4 0.499 0.631 0.730 1.000 ROM5 0.526 0.520 0.628 0.628 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -8565.841 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 ROM1 39.961 0.200 0.000 1.05% 24.242 34.848 39.394 474.000 329.424 -0.145 100.000 0.21% 43.939 54.545 ROM2 35.783 0.300 0.000 2.57% 21.212 30.303 34.848 428.000 315.713 0.218 98.485 0.23% 40.909 50.000 ROM3 37.569 0.105 0.000 2.73% 19.697 33.333 37.879 439.000 346.778 -0.342 90.909 0.23% 42.424 53.030 ROM4 35.456 0.281 0.000 1.24% 18.182 28.333 34.848 404.000 342.699 -0.477 90.909 0.25% 40.909 51.515 ROM5 35.380 0.177 0.000 2.99% 18.182 30.303 34.848 334.000 341.404 -0.439 89.394 0.30% 39.394 51.515 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -8601.208 H0 Scaling Correction Factor 1.3012 for MLR Information Criteria Akaike (AIC) 17216.416 Bayesian (BIC) 17247.536 Sample-Size Adjusted BIC 17225.312 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 37.628 0.653 57.638 0.000 Intercepts ROM1 0.000 0.000 999.000 999.000 ROM2 0.000 0.000 999.000 999.000 ROM3 0.000 0.000 999.000 999.000 ROM4 0.000 0.000 999.000 999.000 ROM5 0.000 0.000 999.000 999.000 Variances P 209.295 14.561 14.374 0.000 Residual Variances ROM1 188.156 17.825 10.556 0.000 ROM2 120.916 15.496 7.803 0.000 ROM3 103.378 12.544 8.241 0.000 ROM4 121.001 11.916 10.155 0.000 ROM5 163.122 18.211 8.957 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.260E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ ROM1 0 ROM2 0 ROM3 0 ROM4 0 ROM5 0 THETA ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1 ROM2 0 2 ROM3 0 0 3 ROM4 0 0 0 4 ROM5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ ROM1 0.000 ROM2 0.000 ROM3 0.000 ROM4 0.000 ROM5 0.000 THETA ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 164.712 ROM2 0.000 157.856 ROM3 0.000 0.000 173.389 ROM4 0.000 0.000 0.000 171.349 ROM5 0.000 0.000 0.000 0.000 170.702 ALPHA P ________ 38.075 BETA P ________ P 0.000 PSI P ________ P 264.409 #Univariate LGCM - IPF Romantic Relationships: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Rom1 Rom2 Rom3 Rom4 Rom5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | Rom1 Rom2 Rom3 Rom4 Rom5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 630 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous ROM1 ROM2 ROM3 ROM4 ROM5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 0.752 ROM2 0.541 0.679 ROM3 0.549 0.551 0.697 ROM4 0.495 0.498 0.543 0.641 ROM5 0.403 0.394 0.413 0.403 0.530 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 40.594 36.749 37.950 36.248 36.300 Covariances ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 335.585 ROM2 190.453 322.111 ROM3 190.343 223.867 345.007 ROM4 171.010 211.897 253.812 350.451 ROM5 182.203 176.607 220.521 222.326 357.831 Correlations ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1.000 ROM2 0.579 1.000 ROM3 0.559 0.672 1.000 ROM4 0.499 0.631 0.730 1.000 ROM5 0.526 0.520 0.628 0.628 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -8565.841 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 ROM1 39.961 0.200 0.000 1.05% 24.242 34.848 39.394 474.000 329.424 -0.145 100.000 0.21% 43.939 54.545 ROM2 35.783 0.300 0.000 2.57% 21.212 30.303 34.848 428.000 315.713 0.218 98.485 0.23% 40.909 50.000 ROM3 37.569 0.105 0.000 2.73% 19.697 33.333 37.879 439.000 346.778 -0.342 90.909 0.23% 42.424 53.030 ROM4 35.456 0.281 0.000 1.24% 18.182 28.333 34.848 404.000 342.699 -0.477 90.909 0.25% 40.909 51.515 ROM5 35.380 0.177 0.000 2.99% 18.182 30.303 34.848 334.000 341.404 -0.439 89.394 0.30% 39.394 51.515 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -8590.155 H0 Scaling Correction Factor 1.2120 for MLR Information Criteria Akaike (AIC) 17200.310 Bayesian (BIC) 17244.767 Sample-Size Adjusted BIC 17213.018 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -6.831 6.461 -1.057 0.290 Means P 42.292 1.350 31.327 0.000 PS -0.485 0.127 -3.820 0.000 Intercepts ROM1 0.000 0.000 999.000 999.000 ROM2 0.000 0.000 999.000 999.000 ROM3 0.000 0.000 999.000 999.000 ROM4 0.000 0.000 999.000 999.000 ROM5 0.000 0.000 999.000 999.000 Variances P 243.408 67.144 3.625 0.000 PS 1.069 0.660 1.619 0.105 Residual Variances ROM1 164.442 19.503 8.432 0.000 ROM2 123.428 15.596 7.914 0.000 ROM3 103.156 12.480 8.266 0.000 ROM4 114.455 12.229 9.359 0.000 ROM5 143.085 20.350 7.031 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.190E-03 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ ROM1 0 0 ROM2 0 0 ROM3 0 0 ROM4 0 0 ROM5 0 0 THETA ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1 ROM2 0 2 ROM3 0 0 3 ROM4 0 0 0 4 ROM5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ ROM1 0.000 0.000 ROM2 0.000 0.000 ROM3 0.000 0.000 ROM4 0.000 0.000 ROM5 0.000 0.000 THETA ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 164.712 ROM2 0.000 157.856 ROM3 0.000 0.000 173.389 ROM4 0.000 0.000 0.000 171.349 ROM5 0.000 0.000 0.000 0.000 170.702 ALPHA P PS ________ ________ 41.472 -0.563 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 936.771 PS 0.000 12.548 #Univariate LGCM - IPF Romantic Relationships: Male quadratic INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Rom1 Rom2 Rom3 Rom4 Rom5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | Rom1 Rom2 Rom3 Rom4 Rom5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 630 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous ROM1 ROM2 ROM3 ROM4 ROM5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 0.752 ROM2 0.541 0.679 ROM3 0.549 0.551 0.697 ROM4 0.495 0.498 0.543 0.641 ROM5 0.403 0.394 0.413 0.403 0.530 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 40.594 36.749 37.950 36.248 36.300 Covariances ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 335.585 ROM2 190.453 322.111 ROM3 190.343 223.867 345.007 ROM4 171.010 211.897 253.812 350.451 ROM5 182.203 176.607 220.521 222.326 357.831 Correlations ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1.000 ROM2 0.579 1.000 ROM3 0.559 0.672 1.000 ROM4 0.499 0.631 0.730 1.000 ROM5 0.526 0.520 0.628 0.628 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -8565.841 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 ROM1 39.961 0.200 0.000 1.05% 24.242 34.848 39.394 474.000 329.424 -0.145 100.000 0.21% 43.939 54.545 ROM2 35.783 0.300 0.000 2.57% 21.212 30.303 34.848 428.000 315.713 0.218 98.485 0.23% 40.909 50.000 ROM3 37.569 0.105 0.000 2.73% 19.697 33.333 37.879 439.000 346.778 -0.342 90.909 0.23% 42.424 53.030 ROM4 35.456 0.281 0.000 1.24% 18.182 28.333 34.848 404.000 342.699 -0.477 90.909 0.25% 40.909 51.515 ROM5 35.380 0.177 0.000 2.99% 18.182 30.303 34.848 334.000 341.404 -0.439 89.394 0.30% 39.394 51.515 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -8585.944 H0 Scaling Correction Factor 1.0728 for MLR Information Criteria Akaike (AIC) 17199.889 Bayesian (BIC) 17262.129 Sample-Size Adjusted BIC 17217.681 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -22.897 31.660 -0.723 0.470 PQ WITH P 0.483 1.241 0.389 0.697 PS -0.383 0.280 -1.369 0.171 Means P 45.370 2.882 15.742 0.000 PS -1.205 0.598 -2.017 0.044 PQ 0.039 0.030 1.285 0.199 Intercepts ROM1 0.000 0.000 999.000 999.000 ROM2 0.000 0.000 999.000 999.000 ROM3 0.000 0.000 999.000 999.000 ROM4 0.000 0.000 999.000 999.000 ROM5 0.000 0.000 999.000 999.000 Variances P 245.442 163.045 1.505 0.132 PS 9.153 6.753 1.355 0.175 PQ 0.020 0.012 1.630 0.103 Residual Variances ROM1 159.356 20.224 7.880 0.000 ROM2 118.631 15.355 7.726 0.000 ROM3 99.627 12.314 8.090 0.000 ROM4 112.166 12.284 9.131 0.000 ROM5 132.585 19.085 6.947 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.238E-07 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ ROM1 0 0 0 ROM2 0 0 0 ROM3 0 0 0 ROM4 0 0 0 ROM5 0 0 0 THETA ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1 ROM2 0 2 ROM3 0 0 3 ROM4 0 0 0 4 ROM5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ ROM1 0.000 0.000 0.000 ROM2 0.000 0.000 0.000 ROM3 0.000 0.000 0.000 ROM4 0.000 0.000 0.000 ROM5 0.000 0.000 0.000 THETA ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 164.712 ROM2 0.000 157.856 ROM3 0.000 0.000 173.389 ROM4 0.000 0.000 0.000 171.349 ROM5 0.000 0.000 0.000 0.000 170.702 ALPHA P PS PQ ________ ________ ________ 39.545 -0.518 -0.033 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 3224.087 PS 0.000 216.769 PQ 0.000 0.000 1.207 #Univariate LGCM - IPF Work: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 599 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous WRK1 WRK2 WRK3 WRK4 WRK5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 0.791 WRK2 0.548 0.676 WRK3 0.524 0.509 0.639 WRK4 0.459 0.439 0.452 0.556 WRK5 0.359 0.351 0.347 0.342 0.456 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 28.519 26.558 26.348 25.890 25.847 Covariances WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 286.609 WRK2 149.749 215.519 WRK3 154.630 166.106 255.202 WRK4 129.028 142.387 162.982 228.540 WRK5 122.758 144.530 162.060 156.186 235.092 Correlations WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1.000 WRK2 0.603 1.000 WRK3 0.572 0.708 1.000 WRK4 0.504 0.642 0.675 1.000 WRK5 0.473 0.642 0.662 0.674 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7385.865 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 WRK1 28.277 0.771 0.000 1.27% 13.492 22.222 25.794 474.000 281.887 0.416 88.889 0.21% 29.365 41.270 WRK2 26.241 0.617 0.000 1.23% 13.492 20.635 24.603 405.000 202.478 0.525 83.333 0.25% 28.571 38.095 WRK3 25.395 0.448 0.000 3.66% 11.111 19.841 24.603 383.000 237.774 -0.206 77.500 0.26% 28.571 38.095 WRK4 24.745 0.631 0.000 2.10% 11.404 19.048 23.016 333.000 220.599 0.430 86.667 0.30% 27.778 37.302 WRK5 24.728 0.627 0.000 1.10% 11.111 18.254 22.807 273.000 230.250 0.111 85.088 0.37% 26.984 37.302 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -7401.709 H0 Scaling Correction Factor 1.4569 for MLR Information Criteria Akaike (AIC) 14817.418 Bayesian (BIC) 14848.185 Sample-Size Adjusted BIC 14825.962 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 26.687 0.570 46.836 0.000 Intercepts WRK1 0.000 0.000 999.000 999.000 WRK2 0.000 0.000 999.000 999.000 WRK3 0.000 0.000 999.000 999.000 WRK4 0.000 0.000 999.000 999.000 WRK5 0.000 0.000 999.000 999.000 Variances P 152.441 13.035 11.695 0.000 Residual Variances WRK1 157.083 15.402 10.199 0.000 WRK2 63.019 8.259 7.630 0.000 WRK3 80.062 10.371 7.720 0.000 WRK4 84.027 9.992 8.410 0.000 WRK5 91.132 14.123 6.453 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.328E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ WRK1 0 WRK2 0 WRK3 0 WRK4 0 WRK5 0 THETA WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1 WRK2 0 2 WRK3 0 0 3 WRK4 0 0 0 4 WRK5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ WRK1 0.000 WRK2 0.000 WRK3 0.000 WRK4 0.000 WRK5 0.000 THETA WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 140.943 WRK2 0.000 101.239 WRK3 0.000 0.000 118.887 WRK4 0.000 0.000 0.000 110.299 WRK5 0.000 0.000 0.000 0.000 115.125 ALPHA P ________ 27.212 BETA P ________ P 0.000 PSI P ________ P 210.623 #Univariate LGCM - IPF Work: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 599 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous WRK1 WRK2 WRK3 WRK4 WRK5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 0.791 WRK2 0.548 0.676 WRK3 0.524 0.509 0.639 WRK4 0.459 0.439 0.452 0.556 WRK5 0.359 0.351 0.347 0.342 0.456 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 28.519 26.558 26.348 25.890 25.847 Covariances WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 286.609 WRK2 149.749 215.519 WRK3 154.630 166.106 255.202 WRK4 129.028 142.387 162.982 228.540 WRK5 122.758 144.530 162.060 156.186 235.092 Correlations WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1.000 WRK2 0.603 1.000 WRK3 0.572 0.708 1.000 WRK4 0.504 0.642 0.675 1.000 WRK5 0.473 0.642 0.662 0.674 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7385.865 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 WRK1 28.277 0.771 0.000 1.27% 13.492 22.222 25.794 474.000 281.887 0.416 88.889 0.21% 29.365 41.270 WRK2 26.241 0.617 0.000 1.23% 13.492 20.635 24.603 405.000 202.478 0.525 83.333 0.25% 28.571 38.095 WRK3 25.395 0.448 0.000 3.66% 11.111 19.841 24.603 383.000 237.774 -0.206 77.500 0.26% 28.571 38.095 WRK4 24.745 0.631 0.000 2.10% 11.404 19.048 23.016 333.000 220.599 0.430 86.667 0.30% 27.778 37.302 WRK5 24.728 0.627 0.000 1.10% 11.111 18.254 22.807 273.000 230.250 0.111 85.088 0.37% 26.984 37.302 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -7391.386 H0 Scaling Correction Factor 1.3732 for MLR Information Criteria Akaike (AIC) 14802.773 Bayesian (BIC) 14846.725 Sample-Size Adjusted BIC 14814.978 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -13.929 6.011 -2.317 0.020 Means P 29.662 1.218 24.355 0.000 PS -0.311 0.116 -2.683 0.007 Intercepts WRK1 0.000 0.000 999.000 999.000 WRK2 0.000 0.000 999.000 999.000 WRK3 0.000 0.000 999.000 999.000 WRK4 0.000 0.000 999.000 999.000 WRK5 0.000 0.000 999.000 999.000 Variances P 274.792 64.824 4.239 0.000 PS 1.544 0.592 2.608 0.009 Residual Variances WRK1 132.463 15.878 8.343 0.000 WRK2 62.627 8.232 7.608 0.000 WRK3 80.943 10.337 7.830 0.000 WRK4 80.304 9.823 8.175 0.000 WRK5 62.929 14.413 4.366 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.115E-02 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ WRK1 0 0 WRK2 0 0 WRK3 0 0 WRK4 0 0 WRK5 0 0 THETA WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1 WRK2 0 2 WRK3 0 0 3 WRK4 0 0 0 4 WRK5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ WRK1 0.000 0.000 WRK2 0.000 0.000 WRK3 0.000 0.000 WRK4 0.000 0.000 WRK5 0.000 0.000 THETA WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 140.943 WRK2 0.000 101.239 WRK3 0.000 0.000 118.887 WRK4 0.000 0.000 0.000 110.299 WRK5 0.000 0.000 0.000 0.000 115.125 ALPHA P PS ________ ________ 30.065 -0.536 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 808.816 PS 0.000 11.324 #Univariate LGCM - IPF Work: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 599 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous WRK1 WRK2 WRK3 WRK4 WRK5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 0.791 WRK2 0.548 0.676 WRK3 0.524 0.509 0.639 WRK4 0.459 0.439 0.452 0.556 WRK5 0.359 0.351 0.347 0.342 0.456 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 28.519 26.558 26.348 25.890 25.847 Covariances WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 286.609 WRK2 149.749 215.519 WRK3 154.630 166.106 255.202 WRK4 129.028 142.387 162.982 228.540 WRK5 122.758 144.530 162.060 156.186 235.092 Correlations WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1.000 WRK2 0.603 1.000 WRK3 0.572 0.708 1.000 WRK4 0.504 0.642 0.675 1.000 WRK5 0.473 0.642 0.662 0.674 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7385.865 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 WRK1 28.277 0.771 0.000 1.27% 13.492 22.222 25.794 474.000 281.887 0.416 88.889 0.21% 29.365 41.270 WRK2 26.241 0.617 0.000 1.23% 13.492 20.635 24.603 405.000 202.478 0.525 83.333 0.25% 28.571 38.095 WRK3 25.395 0.448 0.000 3.66% 11.111 19.841 24.603 383.000 237.774 -0.206 77.500 0.26% 28.571 38.095 WRK4 24.745 0.631 0.000 2.10% 11.404 19.048 23.016 333.000 220.599 0.430 86.667 0.30% 27.778 37.302 WRK5 24.728 0.627 0.000 1.10% 11.111 18.254 22.807 273.000 230.250 0.111 85.088 0.37% 26.984 37.302 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -7388.244 H0 Scaling Correction Factor 1.1874 for MLR Information Criteria Akaike (AIC) 14804.488 Bayesian (BIC) 14866.021 Sample-Size Adjusted BIC 14821.575 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -2.059 11.580 -0.178 0.859 PQ WITH P -0.487 0.389 -1.250 0.211 PS -0.083 0.074 -1.115 0.265 Means P 31.876 2.597 12.274 0.000 PS -0.805 0.527 -1.528 0.126 PQ 0.026 0.026 0.969 0.333 Intercepts WRK1 0.000 0.000 999.000 999.000 WRK2 0.000 0.000 999.000 999.000 WRK3 0.000 0.000 999.000 999.000 WRK4 0.000 0.000 999.000 999.000 WRK5 0.000 0.000 999.000 999.000 Variances P 155.894 81.931 1.903 0.057 PS 2.403 2.048 1.174 0.241 PQ 0.007 0.004 1.785 0.074 Residual Variances WRK1 133.036 15.795 8.423 0.000 WRK2 59.782 8.212 7.280 0.000 WRK3 79.885 10.369 7.704 0.000 WRK4 80.963 9.940 8.145 0.000 WRK5 56.767 14.093 4.028 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.175E-07 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ WRK1 0 0 0 WRK2 0 0 0 WRK3 0 0 0 WRK4 0 0 0 WRK5 0 0 0 THETA WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1 WRK2 0 2 WRK3 0 0 3 WRK4 0 0 0 4 WRK5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ WRK1 0.000 0.000 0.000 WRK2 0.000 0.000 0.000 WRK3 0.000 0.000 0.000 WRK4 0.000 0.000 0.000 WRK5 0.000 0.000 0.000 THETA WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 140.943 WRK2 0.000 101.239 WRK3 0.000 0.000 118.887 WRK4 0.000 0.000 0.000 110.299 WRK5 0.000 0.000 0.000 0.000 115.125 ALPHA P PS PQ ________ ________ ________ 35.737 -5.975 0.672 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 2610.137 PS 0.000 277.074 PQ 0.000 0.000 2.705 #Univariate LGCM - IPF Parent: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Par1 Par2 Par3 Par4 Par5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | Par1 Par2 Par3 Par4 Par5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 583 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous PAR1 PAR2 PAR3 PAR4 PAR5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 30 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 0.794 PAR2 0.607 0.717 PAR3 0.588 0.605 0.708 PAR4 0.535 0.540 0.561 0.652 PAR5 0.434 0.420 0.424 0.425 0.545 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 30.608 27.792 28.578 28.483 27.427 Covariances PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 417.730 PAR2 265.984 394.343 PAR3 260.259 298.564 419.567 PAR4 246.979 275.420 316.775 418.022 PAR5 225.542 246.099 278.310 304.011 400.321 Correlations PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1.000 PAR2 0.655 1.000 PAR3 0.622 0.734 1.000 PAR4 0.591 0.678 0.756 1.000 PAR5 0.552 0.619 0.679 0.743 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -8271.211 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 PAR1 30.602 0.408 0.000 6.05% 13.333 21.667 28.333 463.000 401.222 -0.607 93.333 0.22% 35.000 48.333 PAR2 28.059 0.487 0.000 7.66% 10.000 21.667 26.667 418.000 375.392 -0.382 85.000 0.48% 31.667 46.667 PAR3 28.384 0.514 0.000 6.54% 9.259 20.000 26.667 413.000 395.886 -0.333 95.000 0.24% 31.667 46.667 PAR4 28.186 0.645 0.000 8.68% 10.000 20.000 25.833 380.000 405.526 0.081 93.333 0.26% 31.667 45.000 PAR5 26.411 0.732 0.000 7.23% 8.333 18.333 25.000 318.000 372.160 0.361 98.333 0.31% 30.000 41.667 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -8294.573 H0 Scaling Correction Factor 1.2001 for MLR Information Criteria Akaike (AIC) 16603.146 Bayesian (BIC) 16633.723 Sample-Size Adjusted BIC 16611.501 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 28.618 0.755 37.919 0.000 Intercepts PAR1 0.000 0.000 999.000 999.000 PAR2 0.000 0.000 999.000 999.000 PAR3 0.000 0.000 999.000 999.000 PAR4 0.000 0.000 999.000 999.000 PAR5 0.000 0.000 999.000 999.000 Variances P 277.071 19.329 14.335 0.000 Residual Variances PAR1 194.737 17.852 10.909 0.000 PAR2 122.320 12.822 9.540 0.000 PAR3 107.810 12.620 8.543 0.000 PAR4 115.820 13.069 8.862 0.000 PAR5 145.689 17.013 8.563 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.570E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ PAR1 0 PAR2 0 PAR3 0 PAR4 0 PAR5 0 THETA PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1 PAR2 0 2 PAR3 0 0 3 PAR4 0 0 0 4 PAR5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ PAR1 0.000 PAR2 0.000 PAR3 0.000 PAR4 0.000 PAR5 0.000 THETA PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 200.611 PAR2 0.000 187.696 PAR3 0.000 0.000 197.943 PAR4 0.000 0.000 0.000 202.763 PAR5 0.000 0.000 0.000 0.000 186.080 ALPHA P ________ 28.753 BETA P ________ P 0.000 PSI P ________ P 337.737 #Univariate LGCM - IPF Parent: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Par1 Par2 Par3 Par4 Par5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | Par1 Par2 Par3 Par4 Par5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 583 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous PAR1 PAR2 PAR3 PAR4 PAR5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 30 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 0.794 PAR2 0.607 0.717 PAR3 0.588 0.605 0.708 PAR4 0.535 0.540 0.561 0.652 PAR5 0.434 0.420 0.424 0.425 0.545 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 30.608 27.792 28.578 28.483 27.427 Covariances PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 417.730 PAR2 265.984 394.343 PAR3 260.259 298.564 419.567 PAR4 246.979 275.420 316.775 418.022 PAR5 225.542 246.099 278.310 304.011 400.321 Correlations PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1.000 PAR2 0.655 1.000 PAR3 0.622 0.734 1.000 PAR4 0.591 0.678 0.756 1.000 PAR5 0.552 0.619 0.679 0.743 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -8271.211 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 PAR1 30.602 0.408 0.000 6.05% 13.333 21.667 28.333 463.000 401.222 -0.607 93.333 0.22% 35.000 48.333 PAR2 28.059 0.487 0.000 7.66% 10.000 21.667 26.667 418.000 375.392 -0.382 85.000 0.48% 31.667 46.667 PAR3 28.384 0.514 0.000 6.54% 9.259 20.000 26.667 413.000 395.886 -0.333 95.000 0.24% 31.667 46.667 PAR4 28.186 0.645 0.000 8.68% 10.000 20.000 25.833 380.000 405.526 0.081 93.333 0.26% 31.667 45.000 PAR5 26.411 0.732 0.000 7.23% 8.333 18.333 25.000 318.000 372.160 0.361 98.333 0.31% 30.000 41.667 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -8288.762 H0 Scaling Correction Factor 1.1555 for MLR Information Criteria Akaike (AIC) 16597.524 Bayesian (BIC) 16641.206 Sample-Size Adjusted BIC 16609.460 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -13.153 6.976 -1.885 0.059 Means P 31.613 1.448 21.834 0.000 PS -0.307 0.131 -2.341 0.019 Intercepts PAR1 0.000 0.000 999.000 999.000 PAR2 0.000 0.000 999.000 999.000 PAR3 0.000 0.000 999.000 999.000 PAR4 0.000 0.000 999.000 999.000 PAR5 0.000 0.000 999.000 999.000 Variances P 383.130 76.447 5.012 0.000 PS 1.576 0.733 2.149 0.032 Residual Variances PAR1 170.060 18.160 9.365 0.000 PAR2 122.681 12.894 9.514 0.000 PAR3 109.932 12.606 8.721 0.000 PAR4 109.904 13.203 8.324 0.000 PAR5 115.478 20.951 5.512 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.679E-03 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ PAR1 0 0 PAR2 0 0 PAR3 0 0 PAR4 0 0 PAR5 0 0 THETA PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1 PAR2 0 2 PAR3 0 0 3 PAR4 0 0 0 4 PAR5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ PAR1 0.000 0.000 PAR2 0.000 0.000 PAR3 0.000 0.000 PAR4 0.000 0.000 PAR5 0.000 0.000 THETA PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 200.611 PAR2 0.000 187.696 PAR3 0.000 0.000 197.943 PAR4 0.000 0.000 0.000 202.763 PAR5 0.000 0.000 0.000 0.000 186.080 ALPHA P PS ________ ________ 30.081 0.269 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 983.012 PS 0.000 14.212 #Univariate LGCM - IPF Parent: Male quadratic INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Par1 Par2 Par3 Par4 Par5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | Par1 Par2 Par3 Par4 Par5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 583 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous PAR1 PAR2 PAR3 PAR4 PAR5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 30 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 0.794 PAR2 0.607 0.717 PAR3 0.588 0.605 0.708 PAR4 0.535 0.540 0.561 0.652 PAR5 0.434 0.420 0.424 0.425 0.545 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 30.608 27.792 28.578 28.483 27.427 Covariances PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 417.730 PAR2 265.984 394.343 PAR3 260.259 298.564 419.567 PAR4 246.979 275.420 316.775 418.022 PAR5 225.542 246.099 278.310 304.011 400.321 Correlations PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1.000 PAR2 0.655 1.000 PAR3 0.622 0.734 1.000 PAR4 0.591 0.678 0.756 1.000 PAR5 0.552 0.619 0.679 0.743 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -8271.211 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 PAR1 30.602 0.408 0.000 6.05% 13.333 21.667 28.333 463.000 401.222 -0.607 93.333 0.22% 35.000 48.333 PAR2 28.059 0.487 0.000 7.66% 10.000 21.667 26.667 418.000 375.392 -0.382 85.000 0.48% 31.667 46.667 PAR3 28.384 0.514 0.000 6.54% 9.259 20.000 26.667 413.000 395.886 -0.333 95.000 0.24% 31.667 46.667 PAR4 28.186 0.645 0.000 8.68% 10.000 20.000 25.833 380.000 405.526 0.081 93.333 0.26% 31.667 45.000 PAR5 26.411 0.732 0.000 7.23% 8.333 18.333 25.000 318.000 372.160 0.361 98.333 0.31% 30.000 41.667 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -8282.086 H0 Scaling Correction Factor 1.0004 for MLR Information Criteria Akaike (AIC) 16592.172 Bayesian (BIC) 16653.327 Sample-Size Adjusted BIC 16608.882 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P 2.275 17.302 0.131 0.895 PQ WITH P -0.770 0.585 -1.316 0.188 PS -0.328 0.177 -1.851 0.064 Means P 32.759 2.490 13.158 0.000 PS -0.552 0.518 -1.065 0.287 PQ 0.012 0.027 0.456 0.649 Intercepts PAR1 0.000 0.000 999.000 999.000 PAR2 0.000 0.000 999.000 999.000 PAR3 0.000 0.000 999.000 999.000 PAR4 0.000 0.000 999.000 999.000 PAR5 0.000 0.000 999.000 999.000 Variances P 158.292 99.810 1.586 0.113 PS 7.007 4.132 1.696 0.090 PQ 0.021 0.009 2.398 0.016 Residual Variances PAR1 167.303 17.508 9.556 0.000 PAR2 119.470 12.804 9.331 0.000 PAR3 105.219 12.786 8.230 0.000 PAR4 107.253 12.859 8.340 0.000 PAR5 102.005 19.631 5.196 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.259E-09 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ PAR1 0 0 0 PAR2 0 0 0 PAR3 0 0 0 PAR4 0 0 0 PAR5 0 0 0 THETA PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1 PAR2 0 2 PAR3 0 0 3 PAR4 0 0 0 4 PAR5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ PAR1 0.000 0.000 0.000 PAR2 0.000 0.000 0.000 PAR3 0.000 0.000 0.000 PAR4 0.000 0.000 0.000 PAR5 0.000 0.000 0.000 THETA PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 200.611 PAR2 0.000 187.696 PAR3 0.000 0.000 197.943 PAR4 0.000 0.000 0.000 202.763 PAR5 0.000 0.000 0.000 0.000 186.080 ALPHA P PS PQ ________ ________ ________ 36.247 -2.387 0.272 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 2768.067 PS 0.000 254.892 PQ 0.000 0.000 1.988 #Univariate LGCM - IPF Education: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Edu1 Edu2 Edu3 Edu4 Edu5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | Edu1 Edu2 Edu3 Edu4 Edu5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 384 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous EDU1 EDU2 EDU3 EDU4 EDU5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 0.576 EDU2 0.195 0.430 EDU3 0.172 0.206 0.359 EDU4 0.107 0.115 0.128 0.247 EDU5 0.070 0.073 0.070 0.078 0.180 THE COVARIANCE COVERAGE FALLS BELOW THE SPECIFIED LIMIT. THE MISSING DATA EM ALGORITHM WILL NOT BE INITIATED. CHECK YOUR DATA OR LOWER THE COVARIANCE COVERAGE LIMIT. SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 32.865 29.937 31.464 33.882 29.373 Covariances EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 338.991 EDU2 207.847 366.996 EDU3 201.485 226.138 395.956 EDU4 138.440 151.691 230.020 406.942 EDU5 106.851 228.456 243.180 273.849 377.403 Correlations EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 1.000 EDU2 0.589 1.000 EDU3 0.550 0.593 1.000 EDU4 0.373 0.393 0.573 1.000 EDU5 0.299 0.614 0.629 0.699 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -2939.623 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 EDU1 32.322 0.460 0.000 0.45% 15.556 24.444 30.000 221.000 323.245 -0.523 76.667 0.45% 35.556 48.889 EDU2 29.208 0.779 0.000 1.21% 13.333 20.000 24.444 165.000 364.380 -0.111 74.444 0.61% 30.000 43.333 EDU3 29.936 0.575 0.000 2.90% 11.111 22.222 24.444 138.000 384.188 -0.508 78.889 0.72% 31.111 47.436 EDU4 33.187 0.517 0.000 3.16% 13.333 25.556 31.111 95.000 417.993 -0.480 80.000 1.05% 35.556 50.000 EDU5 27.396 0.857 0.000 5.80% 11.111 22.222 25.556 69.000 333.313 0.557 74.444 1.45% 28.889 38.889 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -2949.547 H0 Scaling Correction Factor 1.3685 for MLR Information Criteria Akaike (AIC) 5913.094 Bayesian (BIC) 5940.748 Sample-Size Adjusted BIC 5918.538 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 31.619 0.917 34.489 0.000 Intercepts EDU1 0.000 0.000 999.000 999.000 EDU2 0.000 0.000 999.000 999.000 EDU3 0.000 0.000 999.000 999.000 EDU4 0.000 0.000 999.000 999.000 EDU5 0.000 0.000 999.000 999.000 Variances P 199.972 26.425 7.568 0.000 Residual Variances EDU1 159.210 26.906 5.917 0.000 EDU2 161.223 31.454 5.126 0.000 EDU3 173.172 46.237 3.745 0.000 EDU4 212.164 60.628 3.499 0.000 EDU5 165.506 48.206 3.433 0.001 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.122E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ EDU1 0 EDU2 0 EDU3 0 EDU4 0 EDU5 0 THETA EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 1 EDU2 0 2 EDU3 0 0 3 EDU4 0 0 0 4 EDU5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ EDU1 0.000 EDU2 0.000 EDU3 0.000 EDU4 0.000 EDU5 0.000 THETA EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 161.622 EDU2 0.000 182.190 EDU3 0.000 0.000 192.094 EDU4 0.000 0.000 0.000 208.996 EDU5 0.000 0.000 0.000 0.000 166.657 ALPHA P ________ 32.081 BETA P ________ P 0.000 PSI P ________ P 331.923 #Univariate LGCM - IPF Education: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Edu1 Edu2 Edu3 Edu4 Edu5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | Edu1 Edu2 Edu3 Edu4 Edu5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 384 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous EDU1 EDU2 EDU3 EDU4 EDU5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 0.576 EDU2 0.195 0.430 EDU3 0.172 0.206 0.359 EDU4 0.107 0.115 0.128 0.247 EDU5 0.070 0.073 0.070 0.078 0.180 THE COVARIANCE COVERAGE FALLS BELOW THE SPECIFIED LIMIT. THE MISSING DATA EM ALGORITHM WILL NOT BE INITIATED. CHECK YOUR DATA OR LOWER THE COVARIANCE COVERAGE LIMIT. SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 32.865 29.937 31.464 33.882 29.373 Covariances EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 338.991 EDU2 207.847 366.996 EDU3 201.485 226.138 395.956 EDU4 138.440 151.691 230.020 406.942 EDU5 106.851 228.456 243.180 273.849 377.403 Correlations EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 1.000 EDU2 0.589 1.000 EDU3 0.550 0.593 1.000 EDU4 0.373 0.393 0.573 1.000 EDU5 0.299 0.614 0.629 0.699 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -2939.623 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 EDU1 32.322 0.460 0.000 0.45% 15.556 24.444 30.000 221.000 323.245 -0.523 76.667 0.45% 35.556 48.889 EDU2 29.208 0.779 0.000 1.21% 13.333 20.000 24.444 165.000 364.380 -0.111 74.444 0.61% 30.000 43.333 EDU3 29.936 0.575 0.000 2.90% 11.111 22.222 24.444 138.000 384.188 -0.508 78.889 0.72% 31.111 47.436 EDU4 33.187 0.517 0.000 3.16% 13.333 25.556 31.111 95.000 417.993 -0.480 80.000 1.05% 35.556 50.000 EDU5 27.396 0.857 0.000 5.80% 11.111 22.222 25.556 69.000 333.313 0.557 74.444 1.45% 28.889 38.889 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -2948.095 H0 Scaling Correction Factor 1.2414 for MLR Information Criteria Akaike (AIC) 5916.190 Bayesian (BIC) 5955.696 Sample-Size Adjusted BIC 5923.968 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -22.473 15.129 -1.485 0.137 Means P 33.282 2.475 13.446 0.000 PS -0.190 0.265 -0.718 0.473 Intercepts EDU1 0.000 0.000 999.000 999.000 EDU2 0.000 0.000 999.000 999.000 EDU3 0.000 0.000 999.000 999.000 EDU4 0.000 0.000 999.000 999.000 EDU5 0.000 0.000 999.000 999.000 Variances P 368.475 158.542 2.324 0.020 PS 2.892 1.622 1.783 0.075 Residual Variances EDU1 140.012 35.149 3.983 0.000 EDU2 161.801 30.902 5.236 0.000 EDU3 169.493 44.021 3.850 0.000 EDU4 189.166 56.588 3.343 0.001 EDU5 91.202 64.208 1.420 0.155 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.273E-03 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ EDU1 0 0 EDU2 0 0 EDU3 0 0 EDU4 0 0 EDU5 0 0 THETA EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 1 EDU2 0 2 EDU3 0 0 3 EDU4 0 0 0 4 EDU5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ EDU1 0.000 0.000 EDU2 0.000 0.000 EDU3 0.000 0.000 EDU4 0.000 0.000 EDU5 0.000 0.000 THETA EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 161.622 EDU2 0.000 182.190 EDU3 0.000 0.000 192.094 EDU4 0.000 0.000 0.000 208.996 EDU5 0.000 0.000 0.000 0.000 166.657 ALPHA P PS ________ ________ 25.444 -0.110 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 1248.132 PS 0.000 18.282 #Univariate LGCM - IPF Education: Male quadratic INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Edu1 Edu2 Edu3 Edu4 Edu5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | Edu1 Edu2 Edu3 Edu4 Edu5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 384 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous EDU1 EDU2 EDU3 EDU4 EDU5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 31 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 0.576 EDU2 0.195 0.430 EDU3 0.172 0.206 0.359 EDU4 0.107 0.115 0.128 0.247 EDU5 0.070 0.073 0.070 0.078 0.180 THE COVARIANCE COVERAGE FALLS BELOW THE SPECIFIED LIMIT. THE MISSING DATA EM ALGORITHM WILL NOT BE INITIATED. CHECK YOUR DATA OR LOWER THE COVARIANCE COVERAGE LIMIT. SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 32.865 29.937 31.464 33.882 29.373 Covariances EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 338.991 EDU2 207.847 366.996 EDU3 201.485 226.138 395.956 EDU4 138.440 151.691 230.020 406.942 EDU5 106.851 228.456 243.180 273.849 377.403 Correlations EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 1.000 EDU2 0.589 1.000 EDU3 0.550 0.593 1.000 EDU4 0.373 0.393 0.573 1.000 EDU5 0.299 0.614 0.629 0.699 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -2939.623 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 EDU1 32.322 0.460 0.000 0.45% 15.556 24.444 30.000 221.000 323.245 -0.523 76.667 0.45% 35.556 48.889 EDU2 29.208 0.779 0.000 1.21% 13.333 20.000 24.444 165.000 364.380 -0.111 74.444 0.61% 30.000 43.333 EDU3 29.936 0.575 0.000 2.90% 11.111 22.222 24.444 138.000 384.188 -0.508 78.889 0.72% 31.111 47.436 EDU4 33.187 0.517 0.000 3.16% 13.333 25.556 31.111 95.000 417.993 -0.480 80.000 1.05% 35.556 50.000 EDU5 27.396 0.857 0.000 5.80% 11.111 22.222 25.556 69.000 333.313 0.557 74.444 1.45% 28.889 38.889 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -2944.416 H0 Scaling Correction Factor 1.0531 for MLR Information Criteria Akaike (AIC) 5916.832 Bayesian (BIC) 5972.141 Sample-Size Adjusted BIC 5927.721 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -38.370 57.881 -0.663 0.507 PQ WITH P 2.050 3.394 0.604 0.546 PS -0.965 0.818 -1.180 0.238 Means P 31.625 4.724 6.695 0.000 PS 0.136 1.104 0.123 0.902 PQ -0.015 0.062 -0.236 0.813 Intercepts EDU1 0.000 0.000 999.000 999.000 EDU2 0.000 0.000 999.000 999.000 EDU3 0.000 0.000 999.000 999.000 EDU4 0.000 0.000 999.000 999.000 EDU5 0.000 0.000 999.000 999.000 Variances P 249.462 216.463 1.152 0.249 PS 16.410 14.794 1.109 0.267 PQ 0.063 0.045 1.421 0.155 Residual Variances EDU1 146.163 33.589 4.352 0.000 EDU2 154.007 31.190 4.938 0.000 EDU3 157.495 45.555 3.457 0.001 EDU4 198.613 57.274 3.468 0.001 EDU5 34.250 49.547 0.691 0.489 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.378E-07 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ EDU1 0 0 0 EDU2 0 0 0 EDU3 0 0 0 EDU4 0 0 0 EDU5 0 0 0 THETA EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 1 EDU2 0 2 EDU3 0 0 3 EDU4 0 0 0 4 EDU5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ EDU1 0.000 0.000 0.000 EDU2 0.000 0.000 0.000 EDU3 0.000 0.000 0.000 EDU4 0.000 0.000 0.000 EDU5 0.000 0.000 0.000 THETA EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 161.622 EDU2 0.000 182.190 EDU3 0.000 0.000 192.094 EDU4 0.000 0.000 0.000 208.996 EDU5 0.000 0.000 0.000 0.000 166.657 ALPHA P PS PQ ________ ________ ________ 32.884 -2.702 0.158 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 5096.774 PS 0.000 664.757 PQ 0.000 0.000 5.957 #Univariate LGCM - IPF Self Care: Male intercept INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Slf1 Slf2 Slf3 Slf4 Slf5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P | Slf1 Slf2 Slf3 Slf4 Slf5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 1 Observed dependent variables Continuous SLF1 SLF2 SLF3 SLF4 SLF5 Continuous latent variables P Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 23 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 0.972 SLF2 0.805 0.829 SLF3 0.802 0.749 0.825 SLF4 0.719 0.677 0.700 0.745 SLF5 0.576 0.533 0.543 0.534 0.596 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 47.544 45.982 46.564 44.630 44.187 Covariances SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 395.876 SLF2 238.451 337.620 SLF3 239.886 253.234 377.829 SLF4 226.238 242.168 273.324 386.884 SLF5 214.353 228.868 251.548 272.380 378.118 Correlations SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1.000 SLF2 0.652 1.000 SLF3 0.620 0.709 1.000 SLF4 0.578 0.670 0.715 1.000 SLF5 0.554 0.641 0.666 0.712 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11615.212 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 SLF1 47.496 -0.047 0.000 0.14% 29.167 41.667 47.917 693.000 398.387 -0.650 97.619 0.14% 54.167 64.583 SLF2 45.600 -0.066 0.000 0.34% 29.167 41.667 45.833 591.000 343.025 -0.296 97.917 0.17% 50.000 60.417 SLF3 46.538 -0.068 0.000 0.51% 29.167 41.667 47.917 588.000 378.921 -0.464 95.833 0.17% 52.083 62.500 SLF4 44.302 0.035 0.000 0.56% 25.000 39.583 45.833 531.000 389.523 -0.459 95.833 0.19% 50.000 60.417 SLF5 43.076 0.014 2.083 0.24% 25.000 37.500 43.750 425.000 368.089 -0.588 93.750 0.24% 50.000 58.333 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -11644.578 H0 Scaling Correction Factor 1.0867 for MLR Information Criteria Akaike (AIC) 23303.156 Bayesian (BIC) 23335.142 Sample-Size Adjusted BIC 23312.915 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 45.976 0.634 72.568 0.000 Intercepts SLF1 0.000 0.000 999.000 999.000 SLF2 0.000 0.000 999.000 999.000 SLF3 0.000 0.000 999.000 999.000 SLF4 0.000 0.000 999.000 999.000 SLF5 0.000 0.000 999.000 999.000 Variances P 245.841 13.838 17.766 0.000 Residual Variances SLF1 181.755 12.197 14.901 0.000 SLF2 100.072 8.462 11.826 0.000 SLF3 110.260 9.137 12.068 0.000 SLF4 126.291 10.769 11.727 0.000 SLF5 143.298 13.579 10.553 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.242E-01 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P ________ SLF1 0 SLF2 0 SLF3 0 SLF4 0 SLF5 0 THETA SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1 SLF2 0 2 SLF3 0 0 3 SLF4 0 0 0 4 SLF5 0 0 0 0 5 ALPHA P ________ 6 BETA P ________ P 0 PSI P ________ P 7 STARTING VALUES NU SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P ________ SLF1 0.000 SLF2 0.000 SLF3 0.000 SLF4 0.000 SLF5 0.000 THETA SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 199.193 SLF2 0.000 171.512 SLF3 0.000 0.000 189.461 SLF4 0.000 0.000 0.000 194.761 SLF5 0.000 0.000 0.000 0.000 184.044 ALPHA P ________ 46.153 BETA P ________ P 0.000 PSI P ________ P 285.803 #Univariate LGCM - IPF Self Care: Male linear INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Slf1 Slf2 Slf3 Slf4 Slf5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS | Slf1 Slf2 Slf3 Slf4 Slf5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous SLF1 SLF2 SLF3 SLF4 SLF5 Continuous latent variables P PS Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 23 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 0.972 SLF2 0.805 0.829 SLF3 0.802 0.749 0.825 SLF4 0.719 0.677 0.700 0.745 SLF5 0.576 0.533 0.543 0.534 0.596 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 47.544 45.982 46.564 44.630 44.187 Covariances SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 395.876 SLF2 238.451 337.620 SLF3 239.886 253.234 377.829 SLF4 226.238 242.168 273.324 386.884 SLF5 214.353 228.868 251.548 272.380 378.118 Correlations SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1.000 SLF2 0.652 1.000 SLF3 0.620 0.709 1.000 SLF4 0.578 0.670 0.715 1.000 SLF5 0.554 0.641 0.666 0.712 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11615.212 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 SLF1 47.496 -0.047 0.000 0.14% 29.167 41.667 47.917 693.000 398.387 -0.650 97.619 0.14% 54.167 64.583 SLF2 45.600 -0.066 0.000 0.34% 29.167 41.667 45.833 591.000 343.025 -0.296 97.917 0.17% 50.000 60.417 SLF3 46.538 -0.068 0.000 0.51% 29.167 41.667 47.917 588.000 378.921 -0.464 95.833 0.17% 52.083 62.500 SLF4 44.302 0.035 0.000 0.56% 25.000 39.583 45.833 531.000 389.523 -0.459 95.833 0.19% 50.000 60.417 SLF5 43.076 0.014 2.083 0.24% 25.000 37.500 43.750 425.000 368.089 -0.588 93.750 0.24% 50.000 58.333 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -11628.894 H0 Scaling Correction Factor 1.0427 for MLR Information Criteria Akaike (AIC) 23277.787 Bayesian (BIC) 23323.482 Sample-Size Adjusted BIC 23291.730 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -13.461 5.112 -2.633 0.008 Means P 50.104 1.170 42.823 0.000 PS -0.435 0.107 -4.068 0.000 Intercepts SLF1 0.000 0.000 999.000 999.000 SLF2 0.000 0.000 999.000 999.000 SLF3 0.000 0.000 999.000 999.000 SLF4 0.000 0.000 999.000 999.000 SLF5 0.000 0.000 999.000 999.000 Variances P 355.195 56.396 6.298 0.000 PS 1.614 0.501 3.224 0.001 Residual Variances SLF1 157.006 13.885 11.308 0.000 SLF2 99.446 8.436 11.789 0.000 SLF3 113.194 9.200 12.304 0.000 SLF4 119.026 10.100 11.785 0.000 SLF5 108.658 15.404 7.054 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.587E-03 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS ________ ________ SLF1 0 0 SLF2 0 0 SLF3 0 0 SLF4 0 0 SLF5 0 0 THETA SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1 SLF2 0 2 SLF3 0 0 3 SLF4 0 0 0 4 SLF5 0 0 0 0 5 ALPHA P PS ________ ________ 6 7 BETA P PS ________ ________ P 0 0 PS 0 0 PSI P PS ________ ________ P 8 PS 9 10 STARTING VALUES NU SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS ________ ________ SLF1 0.000 0.000 SLF2 0.000 0.000 SLF3 0.000 0.000 SLF4 0.000 0.000 SLF5 0.000 0.000 THETA SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 199.193 SLF2 0.000 171.512 SLF3 0.000 0.000 189.461 SLF4 0.000 0.000 0.000 194.761 SLF5 0.000 0.000 0.000 0.000 184.044 ALPHA P PS ________ ________ 48.217 -0.073 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 910.336 PS 0.000 12.494 #Univariate LGCM - IPF Self Care: Male quadratic INPUT INSTRUCTIONS DATA: FILE IS "XX"; VARIABLE: NAMES ARE ID Rom1 Rom2 Rom3 Rom4 Rom5 Fam1 Fam2 Fam3 Fam4 Fam5 Wrk1 Wrk2 Wrk3 Wrk4 Wrk5 Fnd1 Fnd2 Fnd3 Fnd4 Fnd5 Par1 Par2 Par3 Par4 Par5 Slf1 Slf2 Slf3 Slf4 Slf5 Edu1 Edu2 Edu3 Edu4 Edu5 Tot1 Tot2 Tot3 Tot4 Tot5 TSD1 TSD2 TSD3 TSD4 TSD5 PCL1 PCL2 PCL3 PCL4 PCL5 Sex; USEVARIABLES ARE Slf1 Slf2 Slf3 Slf4 Slf5 TSD1 TSD2 TSD3 TSD4 TSD5; TSCORES = TSD1 TSD2 TSD3 TSD4 TSD5; Missing = ALL (999); ANALYSIS: ESTIMATOR = MLR; TYPE = RANDOM; MODEL: P PS PQ | Slf1 Slf2 Slf3 Slf4 Slf5 at TSD1 TSD2 TSD3 TSD4 TSD5; OUTPUT: SAMPSTAT; TECH1; SUMMARY OF ANALYSIS Number of groups 1 Number of observations 713 Number of dependent variables 5 Number of independent variables 0 Number of continuous latent variables 3 Observed dependent variables Continuous SLF1 SLF2 SLF3 SLF4 SLF5 Continuous latent variables P PS PQ Variables with special functions Time scores TSD1 TSD2 TSD3 TSD4 TSD5 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 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) U:\Mplus\Mplus_Male_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 23 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 0.972 SLF2 0.805 0.829 SLF3 0.802 0.749 0.825 SLF4 0.719 0.677 0.700 0.745 SLF5 0.576 0.533 0.543 0.534 0.596 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 47.544 45.982 46.564 44.630 44.187 Covariances SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 395.876 SLF2 238.451 337.620 SLF3 239.886 253.234 377.829 SLF4 226.238 242.168 273.324 386.884 SLF5 214.353 228.868 251.548 272.380 378.118 Correlations SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1.000 SLF2 0.652 1.000 SLF3 0.620 0.709 1.000 SLF4 0.578 0.670 0.715 1.000 SLF5 0.554 0.641 0.666 0.712 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11615.212 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 SLF1 47.496 -0.047 0.000 0.14% 29.167 41.667 47.917 693.000 398.387 -0.650 97.619 0.14% 54.167 64.583 SLF2 45.600 -0.066 0.000 0.34% 29.167 41.667 45.833 591.000 343.025 -0.296 97.917 0.17% 50.000 60.417 SLF3 46.538 -0.068 0.000 0.51% 29.167 41.667 47.917 588.000 378.921 -0.464 95.833 0.17% 52.083 62.500 SLF4 44.302 0.035 0.000 0.56% 25.000 39.583 45.833 531.000 389.523 -0.459 95.833 0.19% 50.000 60.417 SLF5 43.076 0.014 2.083 0.24% 25.000 37.500 43.750 425.000 368.089 -0.588 93.750 0.24% 50.000 58.333 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -11624.964 H0 Scaling Correction Factor 0.8158 for MLR Information Criteria Akaike (AIC) 23277.928 Bayesian (BIC) 23341.901 Sample-Size Adjusted BIC 23297.447 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -1.854 3.871 -0.479 0.632 PQ WITH P -0.719 0.082 -8.742 0.000 PS -0.089 0.009 -9.543 0.000 Means P 48.919 2.228 21.954 0.000 PS -0.179 0.453 -0.395 0.693 PQ -0.013 0.023 -0.559 0.576 Intercepts SLF1 0.000 0.000 999.000 999.000 SLF2 0.000 0.000 999.000 999.000 SLF3 0.000 0.000 999.000 999.000 SLF4 0.000 0.000 999.000 999.000 SLF5 0.000 0.000 999.000 999.000 Variances P 224.370 41.923 5.352 0.000 PS 3.443 0.459 7.505 0.000 PQ 0.005 0.000 16.344 0.000 Residual Variances SLF1 154.990 13.314 11.641 0.000 SLF2 98.112 8.515 11.522 0.000 SLF3 110.905 9.260 11.976 0.000 SLF4 118.181 10.060 11.748 0.000 SLF5 104.536 14.958 6.989 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.167E-07 (ratio of smallest to largest eigenvalue) TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION NU SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 0 0 0 0 0 LAMBDA P PS PQ ________ ________ ________ SLF1 0 0 0 SLF2 0 0 0 SLF3 0 0 0 SLF4 0 0 0 SLF5 0 0 0 THETA SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1 SLF2 0 2 SLF3 0 0 3 SLF4 0 0 0 4 SLF5 0 0 0 0 5 ALPHA P PS PQ ________ ________ ________ 6 7 8 BETA P PS PQ ________ ________ ________ P 0 0 0 PS 0 0 0 PQ 0 0 0 PSI P PS PQ ________ ________ ________ P 9 PS 10 11 PQ 12 13 14 STARTING VALUES NU SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 0.000 0.000 0.000 0.000 0.000 LAMBDA P PS PQ ________ ________ ________ SLF1 0.000 0.000 0.000 SLF2 0.000 0.000 0.000 SLF3 0.000 0.000 0.000 SLF4 0.000 0.000 0.000 SLF5 0.000 0.000 0.000 THETA SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 199.193 SLF2 0.000 171.512 SLF3 0.000 0.000 189.461 SLF4 0.000 0.000 0.000 194.761 SLF5 0.000 0.000 0.000 0.000 184.044 ALPHA P PS PQ ________ ________ ________ 51.641 -3.280 0.314 BETA P PS PQ ________ ________ ________ P 0.000 0.000 0.000 PS 0.000 0.000 0.000 PQ 0.000 0.000 0.000 PSI P PS PQ ________ ________ ________ P 3380.538 PS 0.000 316.383 PQ 0.000 0.000 2.208