#Univariate LGCM - PCL: Female 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 721 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_Fem_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 0.545 PCL2 0.423 0.810 PCL3 0.405 0.669 0.782 PCL4 0.372 0.619 0.620 0.717 PCL5 0.304 0.520 0.512 0.509 0.613 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 39.749 39.399 39.824 36.327 38.459 Covariances PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 413.697 PCL2 314.325 426.274 PCL3 318.193 346.919 432.734 PCL4 299.794 317.003 347.756 415.959 PCL5 265.041 275.143 309.273 308.873 383.100 Correlations PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1.000 PCL2 0.749 1.000 PCL3 0.752 0.808 1.000 PCL4 0.723 0.753 0.820 1.000 PCL5 0.666 0.681 0.760 0.774 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10149.419 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 39.649 -0.070 0.000 1.02% 19.000 35.000 40.000 393.000 405.113 -0.900 80.000 2.04% 47.000 58.000 PCL2 38.702 -0.022 0.000 1.54% 20.000 33.000 39.000 584.000 421.035 -0.921 80.000 1.88% 46.000 57.000 PCL3 39.452 -0.057 0.000 1.24% 19.000 34.000 40.000 564.000 440.769 -0.886 80.000 1.42% 47.000 59.000 PCL4 36.122 0.097 0.000 2.13% 16.000 31.000 36.000 517.000 412.266 -0.787 80.000 1.74% 42.000 55.000 PCL5 36.667 0.001 0.000 0.45% 17.000 31.000 36.500 442.000 381.996 -0.897 80.000 0.23% 43.000 56.000 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -10193.690 H0 Scaling Correction Factor 1.2583 for MLR Information Criteria Akaike (AIC) 20401.380 Bayesian (BIC) 20433.445 Sample-Size Adjusted BIC 20411.218 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 38.816 0.702 55.264 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 319.305 14.995 21.294 0.000 Residual Variances PCL1 128.627 13.999 9.188 0.000 PCL2 107.767 10.842 9.940 0.000 PCL3 76.212 8.226 9.264 0.000 PCL4 94.533 9.211 10.263 0.000 PCL5 117.272 11.355 10.328 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.304E-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 202.557 PCL2 0.000 210.517 PCL3 0.000 0.000 220.384 PCL4 0.000 0.000 0.000 206.133 PCL5 0.000 0.000 0.000 0.000 190.998 ALPHA P ________ 38.932 BETA P ________ P 0.000 PSI P ________ P 353.334 #Univariate LGCM - PCL: Female 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 721 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_Fem_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 0.545 PCL2 0.423 0.810 PCL3 0.405 0.669 0.782 PCL4 0.372 0.619 0.620 0.717 PCL5 0.304 0.520 0.512 0.509 0.613 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 39.749 39.399 39.824 36.327 38.459 Covariances PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 413.697 PCL2 314.325 426.274 PCL3 318.193 346.919 432.734 PCL4 299.794 317.003 347.756 415.959 PCL5 265.041 275.143 309.273 308.873 383.100 Correlations PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1.000 PCL2 0.749 1.000 PCL3 0.752 0.808 1.000 PCL4 0.723 0.753 0.820 1.000 PCL5 0.666 0.681 0.760 0.774 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10149.419 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 39.649 -0.070 0.000 1.02% 19.000 35.000 40.000 393.000 405.113 -0.900 80.000 2.04% 47.000 58.000 PCL2 38.702 -0.022 0.000 1.54% 20.000 33.000 39.000 584.000 421.035 -0.921 80.000 1.88% 46.000 57.000 PCL3 39.452 -0.057 0.000 1.24% 19.000 34.000 40.000 564.000 440.769 -0.886 80.000 1.42% 47.000 59.000 PCL4 36.122 0.097 0.000 2.13% 16.000 31.000 36.000 517.000 412.266 -0.787 80.000 1.74% 42.000 55.000 PCL5 36.667 0.001 0.000 0.45% 17.000 31.000 36.500 442.000 381.996 -0.897 80.000 0.23% 43.000 56.000 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -10178.903 H0 Scaling Correction Factor 1.1647 for MLR Information Criteria Akaike (AIC) 20377.806 Bayesian (BIC) 20423.612 Sample-Size Adjusted BIC 20391.860 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -27.303 6.018 -4.537 0.000 Means P 41.315 1.348 30.657 0.000 PS -0.245 0.115 -2.137 0.033 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 614.739 68.245 9.008 0.000 PS 2.395 0.571 4.196 0.000 Residual Variances PCL1 98.771 14.724 6.708 0.000 PCL2 100.793 10.609 9.501 0.000 PCL3 77.435 8.215 9.426 0.000 PCL4 91.566 9.114 10.047 0.000 PCL5 83.409 13.008 6.412 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.166E-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 202.557 PCL2 0.000 210.517 PCL3 0.000 0.000 220.384 PCL4 0.000 0.000 0.000 206.133 PCL5 0.000 0.000 0.000 0.000 190.998 ALPHA P PS ________ ________ 37.331 0.317 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 983.962 PS 0.000 11.338 #Univariate LGCM - PCL: Female 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 721 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_Fem_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 0.545 PCL2 0.423 0.810 PCL3 0.405 0.669 0.782 PCL4 0.372 0.619 0.620 0.717 PCL5 0.304 0.520 0.512 0.509 0.613 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ 39.749 39.399 39.824 36.327 38.459 Covariances PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 413.697 PCL2 314.325 426.274 PCL3 318.193 346.919 432.734 PCL4 299.794 317.003 347.756 415.959 PCL5 265.041 275.143 309.273 308.873 383.100 Correlations PCL1 PCL2 PCL3 PCL4 PCL5 ________ ________ ________ ________ ________ PCL1 1.000 PCL2 0.749 1.000 PCL3 0.752 0.808 1.000 PCL4 0.723 0.753 0.820 1.000 PCL5 0.666 0.681 0.760 0.774 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10149.419 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 39.649 -0.070 0.000 1.02% 19.000 35.000 40.000 393.000 405.113 -0.900 80.000 2.04% 47.000 58.000 PCL2 38.702 -0.022 0.000 1.54% 20.000 33.000 39.000 584.000 421.035 -0.921 80.000 1.88% 46.000 57.000 PCL3 39.452 -0.057 0.000 1.24% 19.000 34.000 40.000 564.000 440.769 -0.886 80.000 1.42% 47.000 59.000 PCL4 36.122 0.097 0.000 2.13% 16.000 31.000 36.000 517.000 412.266 -0.787 80.000 1.74% 42.000 55.000 PCL5 36.667 0.001 0.000 0.45% 17.000 31.000 36.500 442.000 381.996 -0.897 80.000 0.23% 43.000 56.000 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -10175.760 H0 Scaling Correction Factor 1.1047 for MLR Information Criteria Akaike (AIC) 20379.521 Bayesian (BIC) 20443.650 Sample-Size Adjusted BIC 20399.196 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -30.388 37.224 -0.816 0.414 PQ WITH P 0.194 1.624 0.120 0.905 PS -0.347 0.338 -1.024 0.306 Means P 39.933 2.678 14.909 0.000 PS 0.044 0.516 0.086 0.932 PQ -0.014 0.025 -0.561 0.575 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 516.955 180.096 2.870 0.004 PS 8.694 7.793 1.116 0.265 PQ 0.020 0.015 1.329 0.184 Residual Variances PCL1 96.597 15.194 6.358 0.000 PCL2 98.264 10.565 9.301 0.000 PCL3 74.742 8.376 8.924 0.000 PCL4 91.040 9.306 9.783 0.000 PCL5 75.039 13.156 5.704 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.309E-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 202.557 PCL2 0.000 210.517 PCL3 0.000 0.000 220.384 PCL4 0.000 0.000 0.000 206.133 PCL5 0.000 0.000 0.000 0.000 190.998 ALPHA P PS PQ ________ ________ ________ 34.735 -0.050 -0.001 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 3638.064 PS 0.000 374.871 PQ 0.000 0.000 3.380 #Univariate LGCM - IPF total: Female 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 721 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_Fem_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 18 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 0.997 TOT2 0.874 0.875 TOT3 0.861 0.803 0.864 TOT4 0.778 0.720 0.745 0.781 TOT5 0.664 0.609 0.624 0.599 0.667 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 40.949 39.973 39.884 39.238 38.365 Covariances TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 239.988 TOT2 172.001 243.085 TOT3 160.869 184.858 250.176 TOT4 166.667 175.684 180.012 245.026 TOT5 154.824 158.150 164.351 176.741 237.220 Correlations TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1.000 TOT2 0.712 1.000 TOT3 0.657 0.750 1.000 TOT4 0.687 0.720 0.727 1.000 TOT5 0.649 0.659 0.675 0.733 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11580.225 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 40.940 0.062 2.619 0.14% 26.821 37.449 41.362 719.000 239.067 -0.317 85.977 0.14% 45.355 54.018 TOT2 39.713 0.125 2.787 0.16% 25.871 35.168 39.060 631.000 240.114 -0.297 90.508 0.16% 44.048 53.274 TOT3 39.889 0.186 2.904 0.16% 25.216 35.179 39.281 623.000 253.765 -0.410 86.012 0.16% 43.767 54.066 TOT4 39.307 0.245 0.952 0.18% 25.665 34.589 38.467 563.000 248.698 -0.147 86.887 0.18% 41.851 52.282 TOT5 37.965 0.146 1.646 0.21% 24.314 33.380 37.386 481.000 235.152 -0.365 83.532 0.21% 41.657 50.991 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -11608.679 H0 Scaling Correction Factor 1.2682 for MLR Information Criteria Akaike (AIC) 23231.359 Bayesian (BIC) 23263.423 Sample-Size Adjusted BIC 23241.196 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 39.823 0.516 77.205 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 170.748 9.294 18.372 0.000 Residual Variances TOT1 85.055 6.710 12.676 0.000 TOT2 64.098 5.049 12.694 0.000 TOT3 72.315 5.758 12.558 0.000 TOT4 65.706 7.484 8.779 0.000 TOT5 84.217 6.705 12.560 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.239E-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 119.533 TOT2 0.000 120.057 TOT3 0.000 0.000 126.882 TOT4 0.000 0.000 0.000 124.349 TOT5 0.000 0.000 0.000 0.000 117.576 ALPHA P ________ 39.860 BETA P ________ P 0.000 PSI P ________ P 190.945 #Univariate LGCM - IPF total: Female 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 721 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_Fem_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 18 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 0.997 TOT2 0.874 0.875 TOT3 0.861 0.803 0.864 TOT4 0.778 0.720 0.745 0.781 TOT5 0.664 0.609 0.624 0.599 0.667 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 40.949 39.973 39.884 39.238 38.365 Covariances TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 239.988 TOT2 172.001 243.085 TOT3 160.869 184.858 250.176 TOT4 166.667 175.684 180.012 245.026 TOT5 154.824 158.150 164.351 176.741 237.220 Correlations TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1.000 TOT2 0.712 1.000 TOT3 0.657 0.750 1.000 TOT4 0.687 0.720 0.727 1.000 TOT5 0.649 0.659 0.675 0.733 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11580.225 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 40.940 0.062 2.619 0.14% 26.821 37.449 41.362 719.000 239.067 -0.317 85.977 0.14% 45.355 54.018 TOT2 39.713 0.125 2.787 0.16% 25.871 35.168 39.060 631.000 240.114 -0.297 90.508 0.16% 44.048 53.274 TOT3 39.889 0.186 2.904 0.16% 25.216 35.179 39.281 623.000 253.765 -0.410 86.012 0.16% 43.767 54.066 TOT4 39.307 0.245 0.952 0.18% 25.665 34.589 38.467 563.000 248.698 -0.147 86.887 0.18% 41.851 52.282 TOT5 37.965 0.146 1.646 0.21% 24.314 33.380 37.386 481.000 235.152 -0.365 83.532 0.21% 41.657 50.991 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -11595.333 H0 Scaling Correction Factor 1.2331 for MLR Information Criteria Akaike (AIC) 23210.666 Bayesian (BIC) 23256.472 Sample-Size Adjusted BIC 23224.719 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -6.645 2.725 -2.439 0.015 Means P 42.660 0.850 50.175 0.000 PS -0.304 0.073 -4.155 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 233.935 30.757 7.606 0.000 PS 0.680 0.274 2.487 0.013 Residual Variances TOT1 72.779 8.338 8.729 0.000 TOT2 64.200 5.089 12.616 0.000 TOT3 74.209 5.900 12.577 0.000 TOT4 63.627 7.300 8.716 0.000 TOT5 68.967 8.526 8.089 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.718E-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 119.533 TOT2 0.000 120.057 TOT3 0.000 0.000 126.882 TOT4 0.000 0.000 0.000 124.349 TOT5 0.000 0.000 0.000 0.000 117.576 ALPHA P PS ________ ________ 40.482 0.009 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 459.306 PS 0.000 7.750 #Univariate LGCM - IPF total: Female 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 721 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_Fem_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 18 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 0.997 TOT2 0.874 0.875 TOT3 0.861 0.803 0.864 TOT4 0.778 0.720 0.745 0.781 TOT5 0.664 0.609 0.624 0.599 0.667 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ 40.949 39.973 39.884 39.238 38.365 Covariances TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 239.988 TOT2 172.001 243.085 TOT3 160.869 184.858 250.176 TOT4 166.667 175.684 180.012 245.026 TOT5 154.824 158.150 164.351 176.741 237.220 Correlations TOT1 TOT2 TOT3 TOT4 TOT5 ________ ________ ________ ________ ________ TOT1 1.000 TOT2 0.712 1.000 TOT3 0.657 0.750 1.000 TOT4 0.687 0.720 0.727 1.000 TOT5 0.649 0.659 0.675 0.733 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -11580.225 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 40.940 0.062 2.619 0.14% 26.821 37.449 41.362 719.000 239.067 -0.317 85.977 0.14% 45.355 54.018 TOT2 39.713 0.125 2.787 0.16% 25.871 35.168 39.060 631.000 240.114 -0.297 90.508 0.16% 44.048 53.274 TOT3 39.889 0.186 2.904 0.16% 25.216 35.179 39.281 623.000 253.765 -0.410 86.012 0.16% 43.767 54.066 TOT4 39.307 0.245 0.952 0.18% 25.665 34.589 38.467 563.000 248.698 -0.147 86.887 0.18% 41.851 52.282 TOT5 37.965 0.146 1.646 0.21% 24.314 33.380 37.386 481.000 235.152 -0.365 83.532 0.21% 41.657 50.991 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -11592.582 H0 Scaling Correction Factor 1.1135 for MLR Information Criteria Akaike (AIC) 23213.164 Bayesian (BIC) 23277.293 Sample-Size Adjusted BIC 23232.839 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -10.455 12.258 -0.853 0.394 PQ WITH P 0.235 0.597 0.393 0.694 PS -0.140 0.132 -1.064 0.287 Means P 40.562 1.470 27.584 0.000 PS 0.189 0.301 0.626 0.531 PQ -0.026 0.016 -1.675 0.094 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 223.471 61.523 3.632 0.000 PS 3.119 2.702 1.154 0.248 PQ 0.008 0.007 1.238 0.216 Residual Variances TOT1 71.528 8.144 8.783 0.000 TOT2 63.245 5.039 12.552 0.000 TOT3 73.438 5.859 12.534 0.000 TOT4 63.147 7.338 8.605 0.000 TOT5 65.260 8.538 7.643 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.423E-06 (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 119.533 TOT2 0.000 120.057 TOT3 0.000 0.000 126.882 TOT4 0.000 0.000 0.000 124.349 TOT5 0.000 0.000 0.000 0.000 117.576 ALPHA P PS PQ ________ ________ ________ 41.759 -1.130 0.137 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 1481.735 PS 0.000 170.251 PQ 0.000 0.000 1.749 #Univariate LGCM - IPF family: Female 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 711 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_Fem_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 28 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 0.958 FAM2 0.792 0.817 FAM3 0.775 0.710 0.800 FAM4 0.712 0.640 0.655 0.733 FAM5 0.605 0.543 0.550 0.537 0.629 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 47.910 46.409 46.187 45.446 43.029 Covariances FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 507.248 FAM2 288.856 472.180 FAM3 279.706 326.745 538.172 FAM4 304.551 311.295 345.980 523.799 FAM5 257.783 269.065 286.032 295.165 478.294 Correlations FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1.000 FAM2 0.590 1.000 FAM3 0.535 0.648 1.000 FAM4 0.591 0.626 0.652 1.000 FAM5 0.523 0.566 0.564 0.590 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -12078.375 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 47.727 -0.049 0.000 1.03% 26.190 41.667 47.619 681.000 508.050 -0.708 100.000 0.29% 54.762 69.048 FAM2 45.687 -0.023 0.000 1.20% 26.190 40.476 47.619 581.000 469.698 -0.550 100.000 0.34% 52.381 64.286 FAM3 45.291 0.039 0.000 2.28% 23.810 38.095 45.238 569.000 536.747 -0.669 100.000 0.18% 50.000 64.286 FAM4 44.727 0.089 0.000 2.88% 26.190 38.095 42.857 521.000 526.093 -0.595 100.000 0.19% 50.000 64.286 FAM5 42.513 0.120 0.000 2.24% 21.429 35.714 42.857 447.000 481.545 -0.576 100.000 0.22% 47.619 61.905 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -12101.690 H0 Scaling Correction Factor 1.0785 for MLR Information Criteria Akaike (AIC) 24217.380 Bayesian (BIC) 24249.346 Sample-Size Adjusted BIC 24227.120 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 46.064 0.714 64.474 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 299.170 16.704 17.910 0.000 Residual Variances FAM1 242.113 16.419 14.746 0.000 FAM2 169.075 15.109 11.191 0.000 FAM3 211.721 17.628 12.010 0.000 FAM4 191.125 15.604 12.248 0.000 FAM5 234.687 21.201 11.070 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.337E-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 254.025 FAM2 0.000 234.849 FAM3 0.000 0.000 268.373 FAM4 0.000 0.000 0.000 263.046 FAM5 0.000 0.000 0.000 0.000 240.772 ALPHA P ________ 46.280 BETA P ________ P 0.000 PSI P ________ P 358.697 #Univariate LGCM - IPF family: Female 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 711 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_Fem_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 28 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 0.958 FAM2 0.792 0.817 FAM3 0.775 0.710 0.800 FAM4 0.712 0.640 0.655 0.733 FAM5 0.605 0.543 0.550 0.537 0.629 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 47.910 46.409 46.187 45.446 43.029 Covariances FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 507.248 FAM2 288.856 472.180 FAM3 279.706 326.745 538.172 FAM4 304.551 311.295 345.980 523.799 FAM5 257.783 269.065 286.032 295.165 478.294 Correlations FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1.000 FAM2 0.590 1.000 FAM3 0.535 0.648 1.000 FAM4 0.591 0.626 0.652 1.000 FAM5 0.523 0.566 0.564 0.590 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -12078.375 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 47.727 -0.049 0.000 1.03% 26.190 41.667 47.619 681.000 508.050 -0.708 100.000 0.29% 54.762 69.048 FAM2 45.687 -0.023 0.000 1.20% 26.190 40.476 47.619 581.000 469.698 -0.550 100.000 0.34% 52.381 64.286 FAM3 45.291 0.039 0.000 2.28% 23.810 38.095 45.238 569.000 536.747 -0.669 100.000 0.18% 50.000 64.286 FAM4 44.727 0.089 0.000 2.88% 26.190 38.095 42.857 521.000 526.093 -0.595 100.000 0.19% 50.000 64.286 FAM5 42.513 0.120 0.000 2.24% 21.429 35.714 42.857 447.000 481.545 -0.576 100.000 0.22% 47.619 61.905 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -12091.061 H0 Scaling Correction Factor 1.0568 for MLR Information Criteria Akaike (AIC) 24202.122 Bayesian (BIC) 24247.789 Sample-Size Adjusted BIC 24216.036 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -8.422 6.437 -1.308 0.191 Means P 51.003 1.336 38.169 0.000 PS -0.533 0.121 -4.396 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 389.599 67.951 5.734 0.000 PS 0.748 0.663 1.128 0.260 Residual Variances FAM1 225.556 18.742 12.035 0.000 FAM2 168.495 15.066 11.184 0.000 FAM3 213.205 17.729 12.026 0.000 FAM4 191.552 16.018 11.959 0.000 FAM5 212.242 23.120 9.180 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.221E-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 254.025 FAM2 0.000 234.849 FAM3 0.000 0.000 268.373 FAM4 0.000 0.000 0.000 263.046 FAM5 0.000 0.000 0.000 0.000 240.772 ALPHA P PS ________ ________ 48.030 0.007 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 1160.263 PS 0.000 18.076 #Univariate LGCM - IPF family: Female 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 711 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_Fem_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 28 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 0.958 FAM2 0.792 0.817 FAM3 0.775 0.710 0.800 FAM4 0.712 0.640 0.655 0.733 FAM5 0.605 0.543 0.550 0.537 0.629 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 47.910 46.409 46.187 45.446 43.029 Covariances FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 507.248 FAM2 288.856 472.180 FAM3 279.706 326.745 538.172 FAM4 304.551 311.295 345.980 523.799 FAM5 257.783 269.065 286.032 295.165 478.294 Correlations FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1.000 FAM2 0.590 1.000 FAM3 0.535 0.648 1.000 FAM4 0.591 0.626 0.652 1.000 FAM5 0.523 0.566 0.564 0.590 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -12078.375 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 47.727 -0.049 0.000 1.03% 26.190 41.667 47.619 681.000 508.050 -0.708 100.000 0.29% 54.762 69.048 FAM2 45.687 -0.023 0.000 1.20% 26.190 40.476 47.619 581.000 469.698 -0.550 100.000 0.34% 52.381 64.286 FAM3 45.291 0.039 0.000 2.28% 23.810 38.095 45.238 569.000 536.747 -0.669 100.000 0.18% 50.000 64.286 FAM4 44.727 0.089 0.000 2.88% 26.190 38.095 42.857 521.000 526.093 -0.595 100.000 0.19% 50.000 64.286 FAM5 42.513 0.120 0.000 2.24% 21.429 35.714 42.857 447.000 481.545 -0.576 100.000 0.22% 47.619 61.905 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -12091.061 H0 Scaling Correction Factor 1.0568 for MLR Information Criteria Akaike (AIC) 24202.122 Bayesian (BIC) 24247.789 Sample-Size Adjusted BIC 24216.036 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -8.422 6.437 -1.308 0.191 Means P 51.003 1.336 38.169 0.000 PS -0.533 0.121 -4.396 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 389.599 67.951 5.734 0.000 PS 0.748 0.663 1.128 0.260 Residual Variances FAM1 225.556 18.742 12.035 0.000 FAM2 168.495 15.066 11.184 0.000 FAM3 213.205 17.729 12.026 0.000 FAM4 191.552 16.018 11.959 0.000 FAM5 212.242 23.120 9.180 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.221E-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 254.025 FAM2 0.000 234.849 FAM3 0.000 0.000 268.373 FAM4 0.000 0.000 0.000 263.046 FAM5 0.000 0.000 0.000 0.000 240.772 ALPHA P PS ________ ________ 48.030 0.007 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 1160.263 PS 0.000 18.076 #Univariate LGCM - IPF family: Female 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 711 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_Fem_missing_999_entered.csv Input data format FREE SUMMARY OF DATA Number of missing data patterns 28 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT Covariance Coverage FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 0.958 FAM2 0.792 0.817 FAM3 0.775 0.710 0.800 FAM4 0.712 0.640 0.655 0.733 FAM5 0.605 0.543 0.550 0.537 0.629 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ 47.910 46.409 46.187 45.446 43.029 Covariances FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 507.248 FAM2 288.856 472.180 FAM3 279.706 326.745 538.172 FAM4 304.551 311.295 345.980 523.799 FAM5 257.783 269.065 286.032 295.165 478.294 Correlations FAM1 FAM2 FAM3 FAM4 FAM5 ________ ________ ________ ________ ________ FAM1 1.000 FAM2 0.590 1.000 FAM3 0.535 0.648 1.000 FAM4 0.591 0.626 0.652 1.000 FAM5 0.523 0.566 0.564 0.590 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -12078.375 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 47.727 -0.049 0.000 1.03% 26.190 41.667 47.619 681.000 508.050 -0.708 100.000 0.29% 54.762 69.048 FAM2 45.687 -0.023 0.000 1.20% 26.190 40.476 47.619 581.000 469.698 -0.550 100.000 0.34% 52.381 64.286 FAM3 45.291 0.039 0.000 2.28% 23.810 38.095 45.238 569.000 536.747 -0.669 100.000 0.18% 50.000 64.286 FAM4 44.727 0.089 0.000 2.88% 26.190 38.095 42.857 521.000 526.093 -0.595 100.000 0.19% 50.000 64.286 FAM5 42.513 0.120 0.000 2.24% 21.429 35.714 42.857 447.000 481.545 -0.576 100.000 0.22% 47.619 61.905 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -12088.615 H0 Scaling Correction Factor 0.9078 for MLR Information Criteria Akaike (AIC) 24205.230 Bayesian (BIC) 24269.163 Sample-Size Adjusted BIC 24224.710 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -14.495 23.947 -0.605 0.545 PQ WITH P 0.336 1.259 0.267 0.789 PS -0.256 0.295 -0.866 0.387 Means P 46.438 2.398 19.365 0.000 PS 0.543 0.496 1.094 0.274 PQ -0.057 0.026 -2.216 0.027 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 364.767 112.355 3.247 0.001 PS 5.240 5.651 0.927 0.354 PQ 0.015 0.016 0.967 0.333 Residual Variances FAM1 220.142 16.828 13.082 0.000 FAM2 166.759 15.184 10.983 0.000 FAM3 211.883 17.838 11.878 0.000 FAM4 190.616 15.822 12.048 0.000 FAM5 202.565 21.687 9.341 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.106E-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 254.025 FAM2 0.000 234.849 FAM3 0.000 0.000 268.373 FAM4 0.000 0.000 0.000 263.046 FAM5 0.000 0.000 0.000 0.000 240.772 ALPHA P PS PQ ________ ________ ________ 43.909 0.341 -0.030 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 4058.684 PS 0.000 477.244 PQ 0.000 0.000 4.124 #Univariate LGCM - IPF friend: Female 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 688 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_Fem_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 0.836 FND2 0.667 0.767 FND3 0.645 0.618 0.725 FND4 0.592 0.564 0.573 0.682 FND5 0.506 0.483 0.480 0.475 0.596 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 43.120 41.434 41.380 41.254 39.145 Covariances FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 414.732 FND2 243.390 414.680 FND3 210.245 269.751 421.485 FND4 232.937 251.682 267.349 391.272 FND5 216.306 220.266 244.741 249.048 371.425 Correlations FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1.000 FND2 0.587 1.000 FND3 0.503 0.645 1.000 FND4 0.578 0.625 0.658 1.000 FND5 0.551 0.561 0.619 0.653 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10434.751 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 41.966 0.043 0.000 1.57% 22.917 37.500 43.750 575.000 412.257 -0.544 97.917 0.17% 47.917 58.333 FND2 39.770 0.154 0.000 1.14% 20.833 33.333 38.839 528.000 401.005 -0.545 100.000 0.19% 45.833 56.250 FND3 39.669 0.310 0.000 1.20% 20.833 35.417 39.583 499.000 425.935 -0.262 100.000 0.20% 43.750 56.250 FND4 40.631 0.116 0.000 2.13% 22.917 35.417 41.667 469.000 392.114 -0.307 100.000 0.21% 45.833 56.250 FND5 37.891 0.121 0.000 2.20% 20.833 31.250 37.500 410.000 371.561 -0.407 87.500 0.49% 43.750 52.083 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -10456.646 H0 Scaling Correction Factor 1.0803 for MLR Information Criteria Akaike (AIC) 20927.292 Bayesian (BIC) 20959.028 Sample-Size Adjusted BIC 20936.802 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 41.307 0.658 62.754 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 240.967 15.286 15.764 0.000 Residual Variances FND1 207.961 17.071 12.182 0.000 FND2 161.564 13.703 11.791 0.000 FND3 162.569 13.570 11.980 0.000 FND4 131.905 13.148 10.032 0.000 FND5 153.506 13.509 11.363 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 206.129 FND2 0.000 200.502 FND3 0.000 0.000 212.967 FND4 0.000 0.000 0.000 196.057 FND5 0.000 0.000 0.000 0.000 185.781 ALPHA P ________ 41.806 BETA P ________ P 0.000 PSI P ________ P 298.950 #Univariate LGCM - IPF friend: Female 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 688 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_Fem_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 0.836 FND2 0.667 0.767 FND3 0.645 0.618 0.725 FND4 0.592 0.564 0.573 0.682 FND5 0.506 0.483 0.480 0.475 0.596 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 43.120 41.434 41.380 41.254 39.145 Covariances FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 414.732 FND2 243.390 414.680 FND3 210.245 269.751 421.485 FND4 232.937 251.682 267.349 391.272 FND5 216.306 220.266 244.741 249.048 371.425 Correlations FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1.000 FND2 0.587 1.000 FND3 0.503 0.645 1.000 FND4 0.578 0.625 0.658 1.000 FND5 0.551 0.561 0.619 0.653 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10434.751 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 41.966 0.043 0.000 1.57% 22.917 37.500 43.750 575.000 412.257 -0.544 97.917 0.17% 47.917 58.333 FND2 39.770 0.154 0.000 1.14% 20.833 33.333 38.839 528.000 401.005 -0.545 100.000 0.19% 45.833 56.250 FND3 39.669 0.310 0.000 1.20% 20.833 35.417 39.583 499.000 425.935 -0.262 100.000 0.20% 43.750 56.250 FND4 40.631 0.116 0.000 2.13% 22.917 35.417 41.667 469.000 392.114 -0.307 100.000 0.21% 45.833 56.250 FND5 37.891 0.121 0.000 2.20% 20.833 31.250 37.500 410.000 371.561 -0.407 87.500 0.49% 43.750 52.083 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -10456.646 H0 Scaling Correction Factor 1.0803 for MLR Information Criteria Akaike (AIC) 20927.292 Bayesian (BIC) 20959.028 Sample-Size Adjusted BIC 20936.802 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 41.307 0.658 62.754 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 240.967 15.286 15.764 0.000 Residual Variances FND1 207.961 17.071 12.182 0.000 FND2 161.564 13.703 11.791 0.000 FND3 162.569 13.570 11.980 0.000 FND4 131.905 13.148 10.032 0.000 FND5 153.506 13.509 11.363 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 206.129 FND2 0.000 200.502 FND3 0.000 0.000 212.967 FND4 0.000 0.000 0.000 196.057 FND5 0.000 0.000 0.000 0.000 185.781 ALPHA P ________ 41.806 BETA P ________ P 0.000 PSI P ________ P 298.950 #Univariate LGCM - IPF friend: Female 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 688 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_Fem_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 0.836 FND2 0.667 0.767 FND3 0.645 0.618 0.725 FND4 0.592 0.564 0.573 0.682 FND5 0.506 0.483 0.480 0.475 0.596 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 43.120 41.434 41.380 41.254 39.145 Covariances FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 414.732 FND2 243.390 414.680 FND3 210.245 269.751 421.485 FND4 232.937 251.682 267.349 391.272 FND5 216.306 220.266 244.741 249.048 371.425 Correlations FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1.000 FND2 0.587 1.000 FND3 0.503 0.645 1.000 FND4 0.578 0.625 0.658 1.000 FND5 0.551 0.561 0.619 0.653 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10434.751 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 41.966 0.043 0.000 1.57% 22.917 37.500 43.750 575.000 412.257 -0.544 97.917 0.17% 47.917 58.333 FND2 39.770 0.154 0.000 1.14% 20.833 33.333 38.839 528.000 401.005 -0.545 100.000 0.19% 45.833 56.250 FND3 39.669 0.310 0.000 1.20% 20.833 35.417 39.583 499.000 425.935 -0.262 100.000 0.20% 43.750 56.250 FND4 40.631 0.116 0.000 2.13% 22.917 35.417 41.667 469.000 392.114 -0.307 100.000 0.21% 45.833 56.250 FND5 37.891 0.121 0.000 2.20% 20.833 31.250 37.500 410.000 371.561 -0.407 87.500 0.49% 43.750 52.083 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -10447.401 H0 Scaling Correction Factor 1.0611 for MLR Information Criteria Akaike (AIC) 20914.801 Bayesian (BIC) 20960.139 Sample-Size Adjusted BIC 20928.388 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -11.746 5.725 -2.052 0.040 Means P 45.320 1.298 34.922 0.000 PS -0.423 0.117 -3.611 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 351.536 62.222 5.650 0.000 PS 1.228 0.576 2.132 0.033 Residual Variances FND1 183.124 19.866 9.218 0.000 FND2 160.805 13.613 11.813 0.000 FND3 164.211 13.629 12.049 0.000 FND4 131.103 13.176 9.950 0.000 FND5 127.263 16.786 7.581 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.541E-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 206.129 FND2 0.000 200.502 FND3 0.000 0.000 212.967 FND4 0.000 0.000 0.000 196.057 FND5 0.000 0.000 0.000 0.000 185.781 ALPHA P PS ________ ________ 43.610 -0.536 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 968.958 PS 0.000 12.671 #Univariate LGCM - IPF friend: Female 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 688 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_Fem_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 0.836 FND2 0.667 0.767 FND3 0.645 0.618 0.725 FND4 0.592 0.564 0.573 0.682 FND5 0.506 0.483 0.480 0.475 0.596 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ 43.120 41.434 41.380 41.254 39.145 Covariances FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 414.732 FND2 243.390 414.680 FND3 210.245 269.751 421.485 FND4 232.937 251.682 267.349 391.272 FND5 216.306 220.266 244.741 249.048 371.425 Correlations FND1 FND2 FND3 FND4 FND5 ________ ________ ________ ________ ________ FND1 1.000 FND2 0.587 1.000 FND3 0.503 0.645 1.000 FND4 0.578 0.625 0.658 1.000 FND5 0.551 0.561 0.619 0.653 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -10434.751 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 41.966 0.043 0.000 1.57% 22.917 37.500 43.750 575.000 412.257 -0.544 97.917 0.17% 47.917 58.333 FND2 39.770 0.154 0.000 1.14% 20.833 33.333 38.839 528.000 401.005 -0.545 100.000 0.19% 45.833 56.250 FND3 39.669 0.310 0.000 1.20% 20.833 35.417 39.583 499.000 425.935 -0.262 100.000 0.20% 43.750 56.250 FND4 40.631 0.116 0.000 2.13% 22.917 35.417 41.667 469.000 392.114 -0.307 100.000 0.21% 45.833 56.250 FND5 37.891 0.121 0.000 2.20% 20.833 31.250 37.500 410.000 371.561 -0.407 87.500 0.49% 43.750 52.083 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -10445.840 H0 Scaling Correction Factor 0.9132 for MLR Information Criteria Akaike (AIC) 20919.680 Bayesian (BIC) 20983.153 Sample-Size Adjusted BIC 20938.701 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -48.742 29.374 -1.659 0.097 PQ WITH P 1.702 1.273 1.338 0.181 PS -0.429 0.264 -1.624 0.104 Means P 46.235 2.504 18.466 0.000 PS -0.632 0.506 -1.249 0.212 PQ 0.011 0.025 0.430 0.667 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 495.763 149.585 3.314 0.001 PS 10.516 6.071 1.732 0.083 PQ 0.019 0.012 1.677 0.094 Residual Variances FND1 173.747 19.221 9.039 0.000 FND2 160.394 13.713 11.696 0.000 FND3 162.489 13.605 11.944 0.000 FND4 129.792 13.343 9.728 0.000 FND5 126.978 14.223 8.928 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.292E-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 206.129 FND2 0.000 200.502 FND3 0.000 0.000 212.967 FND4 0.000 0.000 0.000 196.057 FND5 0.000 0.000 0.000 0.000 185.781 ALPHA P PS PQ ________ ________ ________ 39.645 0.609 -0.076 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 3598.619 PS 0.000 422.292 PQ 0.000 0.000 3.887 #Univariate LGCM - IPF romantic relationships: Female 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 596 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_Fem_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 0.740 ROM2 0.522 0.669 ROM3 0.502 0.512 0.654 ROM4 0.450 0.438 0.470 0.586 ROM5 0.413 0.366 0.394 0.378 0.522 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 39.817 38.302 37.650 38.202 37.729 Covariances ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 352.238 ROM2 176.296 368.345 ROM3 163.449 228.632 363.701 ROM4 171.166 200.690 237.317 345.033 ROM5 176.284 197.866 207.923 238.843 378.809 Correlations ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1.000 ROM2 0.489 1.000 ROM3 0.457 0.625 1.000 ROM4 0.491 0.563 0.670 1.000 ROM5 0.483 0.530 0.560 0.661 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7918.623 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 ROM1 39.131 0.121 0.000 1.13% 22.727 33.333 39.394 441.000 347.690 -0.417 92.424 0.23% 43.939 54.545 ROM2 38.069 0.241 0.000 0.50% 19.697 30.303 36.364 399.000 375.781 -0.566 95.455 0.25% 42.424 56.061 ROM3 37.035 0.276 0.000 0.77% 19.697 30.303 36.364 390.000 362.445 -0.406 96.970 0.26% 40.909 53.030 ROM4 37.054 0.125 0.000 1.43% 19.697 31.818 36.364 349.000 347.705 -0.540 96.970 0.29% 42.424 54.545 ROM5 36.124 0.390 0.000 0.64% 19.697 28.788 33.333 311.000 379.888 -0.341 95.455 0.64% 39.394 53.030 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -7936.537 H0 Scaling Correction Factor 1.0710 for MLR Information Criteria Akaike (AIC) 15887.073 Bayesian (BIC) 15917.805 Sample-Size Adjusted BIC 15895.582 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 38.313 0.672 57.020 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 203.481 15.017 13.550 0.000 Residual Variances ROM1 210.427 19.231 10.942 0.000 ROM2 164.014 16.419 9.989 0.000 ROM3 140.440 14.390 9.760 0.000 ROM4 121.343 14.146 8.578 0.000 ROM5 167.379 16.658 10.048 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.218E-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 173.845 ROM2 0.000 187.890 ROM3 0.000 0.000 181.222 ROM4 0.000 0.000 0.000 173.853 ROM5 0.000 0.000 0.000 0.000 189.944 ALPHA P ________ 38.685 BETA P ________ P 0.000 PSI P ________ P 267.588 #Univariate LGCM - IPF romantic relationships: Female 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 596 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_Fem_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 0.740 ROM2 0.522 0.669 ROM3 0.502 0.512 0.654 ROM4 0.450 0.438 0.470 0.586 ROM5 0.413 0.366 0.394 0.378 0.522 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 39.817 38.302 37.650 38.202 37.729 Covariances ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 352.238 ROM2 176.296 368.345 ROM3 163.449 228.632 363.701 ROM4 171.166 200.690 237.317 345.033 ROM5 176.284 197.866 207.923 238.843 378.809 Correlations ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1.000 ROM2 0.489 1.000 ROM3 0.457 0.625 1.000 ROM4 0.491 0.563 0.670 1.000 ROM5 0.483 0.530 0.560 0.661 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7918.623 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 ROM1 39.131 0.121 0.000 1.13% 22.727 33.333 39.394 441.000 347.690 -0.417 92.424 0.23% 43.939 54.545 ROM2 38.069 0.241 0.000 0.50% 19.697 30.303 36.364 399.000 375.781 -0.566 95.455 0.25% 42.424 56.061 ROM3 37.035 0.276 0.000 0.77% 19.697 30.303 36.364 390.000 362.445 -0.406 96.970 0.26% 40.909 53.030 ROM4 37.054 0.125 0.000 1.43% 19.697 31.818 36.364 349.000 347.705 -0.540 96.970 0.29% 42.424 54.545 ROM5 36.124 0.390 0.000 0.64% 19.697 28.788 33.333 311.000 379.888 -0.341 95.455 0.64% 39.394 53.030 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -7930.900 H0 Scaling Correction Factor 1.0366 for MLR Information Criteria Akaike (AIC) 15881.801 Bayesian (BIC) 15925.703 Sample-Size Adjusted BIC 15893.956 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -8.752 6.727 -1.301 0.193 Means P 40.346 1.404 28.728 0.000 PS -0.213 0.137 -1.552 0.121 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 247.132 69.006 3.581 0.000 PS 1.352 0.700 1.930 0.054 Residual Variances ROM1 190.270 20.612 9.231 0.000 ROM2 165.687 16.374 10.119 0.000 ROM3 143.229 14.475 9.895 0.000 ROM4 114.030 13.859 8.228 0.000 ROM5 138.918 20.456 6.791 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.326E-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 173.845 ROM2 0.000 187.890 ROM3 0.000 0.000 181.222 ROM4 0.000 0.000 0.000 173.853 ROM5 0.000 0.000 0.000 0.000 189.944 ALPHA P PS ________ ________ 40.790 -0.813 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 917.674 PS 0.000 15.383 #Univariate LGCM - IPF romantic relationships: Female 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 596 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_Fem_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 0.740 ROM2 0.522 0.669 ROM3 0.502 0.512 0.654 ROM4 0.450 0.438 0.470 0.586 ROM5 0.413 0.366 0.394 0.378 0.522 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ 39.817 38.302 37.650 38.202 37.729 Covariances ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 352.238 ROM2 176.296 368.345 ROM3 163.449 228.632 363.701 ROM4 171.166 200.690 237.317 345.033 ROM5 176.284 197.866 207.923 238.843 378.809 Correlations ROM1 ROM2 ROM3 ROM4 ROM5 ________ ________ ________ ________ ________ ROM1 1.000 ROM2 0.489 1.000 ROM3 0.457 0.625 1.000 ROM4 0.491 0.563 0.670 1.000 ROM5 0.483 0.530 0.560 0.661 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7918.623 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 ROM1 39.131 0.121 0.000 1.13% 22.727 33.333 39.394 441.000 347.690 -0.417 92.424 0.23% 43.939 54.545 ROM2 38.069 0.241 0.000 0.50% 19.697 30.303 36.364 399.000 375.781 -0.566 95.455 0.25% 42.424 56.061 ROM3 37.035 0.276 0.000 0.77% 19.697 30.303 36.364 390.000 362.445 -0.406 96.970 0.26% 40.909 53.030 ROM4 37.054 0.125 0.000 1.43% 19.697 31.818 36.364 349.000 347.705 -0.540 96.970 0.29% 42.424 54.545 ROM5 36.124 0.390 0.000 0.64% 19.697 28.788 33.333 311.000 379.888 -0.341 95.455 0.64% 39.394 53.030 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -7929.053 H0 Scaling Correction Factor 0.9009 for MLR Information Criteria Akaike (AIC) 15886.106 Bayesian (BIC) 15947.569 Sample-Size Adjusted BIC 15903.123 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -6.864 14.812 -0.463 0.643 PQ WITH P -0.290 0.497 -0.583 0.560 PS -0.170 0.114 -1.490 0.136 Means P 40.889 2.726 14.999 0.000 PS -0.358 0.581 -0.616 0.538 PQ 0.009 0.030 0.281 0.779 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 183.336 89.666 2.045 0.041 PS 4.758 3.040 1.565 0.118 PQ 0.010 0.005 1.948 0.051 Residual Variances ROM1 188.397 20.731 9.088 0.000 ROM2 161.803 16.561 9.770 0.000 ROM3 139.758 14.502 9.637 0.000 ROM4 112.015 14.013 7.994 0.000 ROM5 131.967 20.123 6.558 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.150E-06 (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 173.845 ROM2 0.000 187.890 ROM3 0.000 0.000 181.222 ROM4 0.000 0.000 0.000 173.853 ROM5 0.000 0.000 0.000 0.000 189.944 ALPHA P PS PQ ________ ________ ________ 38.895 0.122 -0.074 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 3208.768 PS 0.000 270.519 PQ 0.000 0.000 1.670 #Univariate LGCM - IPF work: Female 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 603 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_Fem_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 0.723 WRK2 0.501 0.668 WRK3 0.491 0.521 0.650 WRK4 0.434 0.463 0.476 0.594 WRK5 0.380 0.375 0.388 0.375 0.509 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 27.400 26.704 26.639 26.685 26.158 Covariances WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 243.496 WRK2 151.775 250.774 WRK3 156.785 163.922 260.703 WRK4 146.330 132.913 167.038 230.415 WRK5 142.423 149.746 169.767 157.934 262.920 Correlations WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1.000 WRK2 0.614 1.000 WRK3 0.622 0.641 1.000 WRK4 0.618 0.553 0.682 1.000 WRK5 0.563 0.583 0.648 0.642 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7517.447 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 27.256 0.682 0.000 2.29% 13.492 22.222 26.190 436.000 245.275 0.842 96.825 0.23% 30.000 39.683 WRK2 25.556 0.788 0.000 1.49% 11.905 19.841 23.810 403.000 238.823 0.700 88.095 0.25% 26.667 38.095 WRK3 25.669 0.809 0.000 1.28% 12.698 19.841 23.016 392.000 243.174 0.532 79.365 0.26% 27.778 37.500 WRK4 25.795 0.771 0.794 0.28% 13.492 21.429 24.603 358.000 220.859 0.806 84.127 0.28% 27.778 38.095 WRK5 24.860 0.885 0.000 1.30% 11.111 19.048 22.222 307.000 252.803 0.448 77.778 0.33% 25.397 38.095 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -7525.989 H0 Scaling Correction Factor 1.4748 for MLR Information Criteria Akaike (AIC) 15065.978 Bayesian (BIC) 15096.792 Sample-Size Adjusted BIC 15074.569 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 26.805 0.570 47.002 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 153.820 12.871 11.951 0.000 Residual Variances WRK1 97.762 11.577 8.445 0.000 WRK2 105.597 12.743 8.287 0.000 WRK3 85.420 10.949 7.802 0.000 WRK4 83.142 10.079 8.249 0.000 WRK5 106.821 13.754 7.766 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.387E-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 122.637 WRK2 0.000 119.412 WRK3 0.000 0.000 121.587 WRK4 0.000 0.000 0.000 110.429 WRK5 0.000 0.000 0.000 0.000 126.402 ALPHA P ________ 27.165 BETA P ________ P 0.000 PSI P ________ P 203.521 #Univariate LGCM - IPF work: Female 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 603 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_Fem_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 0.723 WRK2 0.501 0.668 WRK3 0.491 0.521 0.650 WRK4 0.434 0.463 0.476 0.594 WRK5 0.380 0.375 0.388 0.375 0.509 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 27.400 26.704 26.639 26.685 26.158 Covariances WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 243.496 WRK2 151.775 250.774 WRK3 156.785 163.922 260.703 WRK4 146.330 132.913 167.038 230.415 WRK5 142.423 149.746 169.767 157.934 262.920 Correlations WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1.000 WRK2 0.614 1.000 WRK3 0.622 0.641 1.000 WRK4 0.618 0.553 0.682 1.000 WRK5 0.563 0.583 0.648 0.642 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7517.447 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 27.256 0.682 0.000 2.29% 13.492 22.222 26.190 436.000 245.275 0.842 96.825 0.23% 30.000 39.683 WRK2 25.556 0.788 0.000 1.49% 11.905 19.841 23.810 403.000 238.823 0.700 88.095 0.25% 26.667 38.095 WRK3 25.669 0.809 0.000 1.28% 12.698 19.841 23.016 392.000 243.174 0.532 79.365 0.26% 27.778 37.500 WRK4 25.795 0.771 0.794 0.28% 13.492 21.429 24.603 358.000 220.859 0.806 84.127 0.28% 27.778 38.095 WRK5 24.860 0.885 0.000 1.30% 11.111 19.048 22.222 307.000 252.803 0.448 77.778 0.33% 25.397 38.095 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -7523.291 H0 Scaling Correction Factor 1.3748 for MLR Information Criteria Akaike (AIC) 15066.583 Bayesian (BIC) 15110.602 Sample-Size Adjusted BIC 15078.854 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -8.031 5.159 -1.557 0.120 Means P 27.741 1.136 24.414 0.000 PS -0.099 0.108 -0.909 0.363 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 222.764 54.965 4.053 0.000 PS 0.913 0.506 1.805 0.071 Residual Variances WRK1 83.088 12.686 6.550 0.000 WRK2 105.006 12.630 8.314 0.000 WRK3 86.338 11.002 7.847 0.000 WRK4 81.397 10.214 7.969 0.000 WRK5 89.671 15.332 5.848 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.650E-03 (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 122.637 WRK2 0.000 119.412 WRK3 0.000 0.000 121.587 WRK4 0.000 0.000 0.000 110.429 WRK5 0.000 0.000 0.000 0.000 126.402 ALPHA P PS ________ ________ 25.361 -0.157 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 654.189 PS 0.000 11.625 #Univariate LGCM - IPF work: Female 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 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 603 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_Fem_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 0.723 WRK2 0.501 0.668 WRK3 0.491 0.521 0.650 WRK4 0.434 0.463 0.476 0.594 WRK5 0.380 0.375 0.388 0.375 0.509 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ 27.400 26.704 26.639 26.685 26.158 Covariances WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 243.496 WRK2 151.775 250.774 WRK3 156.785 163.922 260.703 WRK4 146.330 132.913 167.038 230.415 WRK5 142.423 149.746 169.767 157.934 262.920 Correlations WRK1 WRK2 WRK3 WRK4 WRK5 ________ ________ ________ ________ ________ WRK1 1.000 WRK2 0.614 1.000 WRK3 0.622 0.641 1.000 WRK4 0.618 0.553 0.682 1.000 WRK5 0.563 0.583 0.648 0.642 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7517.447 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 27.256 0.682 0.000 2.29% 13.492 22.222 26.190 436.000 245.275 0.842 96.825 0.23% 30.000 39.683 WRK2 25.556 0.788 0.000 1.49% 11.905 19.841 23.810 403.000 238.823 0.700 88.095 0.25% 26.667 38.095 WRK3 25.669 0.809 0.000 1.28% 12.698 19.841 23.016 392.000 243.174 0.532 79.365 0.26% 27.778 37.500 WRK4 25.795 0.771 0.794 0.28% 13.492 21.429 24.603 358.000 220.859 0.806 84.127 0.28% 27.778 38.095 WRK5 24.860 0.885 0.000 1.30% 11.111 19.048 22.222 307.000 252.803 0.448 77.778 0.33% 25.397 38.095 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -7522.904 H0 Scaling Correction Factor 1.2061 for MLR Information Criteria Akaike (AIC) 15073.808 Bayesian (BIC) 15135.435 Sample-Size Adjusted BIC 15090.989 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -16.744 20.412 -0.820 0.412 PQ WITH P 0.327 0.794 0.411 0.681 PS -0.124 0.161 -0.771 0.441 Means P 26.633 2.133 12.489 0.000 PS 0.168 0.434 0.386 0.700 PQ -0.014 0.022 -0.655 0.512 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 249.371 113.582 2.196 0.028 PS 3.722 4.068 0.915 0.360 PQ 0.006 0.006 0.876 0.381 Residual Variances WRK1 79.675 11.932 6.677 0.000 WRK2 104.649 12.653 8.270 0.000 WRK3 85.380 11.009 7.755 0.000 WRK4 80.378 10.370 7.751 0.000 WRK5 88.901 14.617 6.082 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.525E-06 (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 122.637 WRK2 0.000 119.412 WRK3 0.000 0.000 121.587 WRK4 0.000 0.000 0.000 110.429 WRK5 0.000 0.000 0.000 0.000 126.402 ALPHA P PS PQ ________ ________ ________ 21.373 0.172 0.052 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 2785.070 PS 0.000 422.897 PQ 0.000 0.000 4.024 #Univariate LGCM - IPF parent: Female 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 539 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_Fem_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 PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 0.755 PAR2 0.566 0.688 PAR3 0.564 0.571 0.707 PAR4 0.512 0.494 0.532 0.636 PAR5 0.427 0.417 0.442 0.427 0.560 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 28.102 27.538 28.114 26.327 26.174 Covariances PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 404.737 PAR2 270.418 403.645 PAR3 241.970 281.812 390.943 PAR4 221.846 229.153 254.236 350.635 PAR5 194.445 209.371 210.572 200.018 338.662 Correlations PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1.000 PAR2 0.669 1.000 PAR3 0.608 0.709 1.000 PAR4 0.589 0.609 0.687 1.000 PAR5 0.525 0.566 0.579 0.580 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7507.859 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 28.384 0.472 0.000 7.13% 10.000 20.000 26.667 407.000 390.939 -0.526 85.000 0.25% 31.667 46.667 PAR2 27.277 0.595 0.000 6.20% 8.333 18.333 25.000 371.000 388.583 -0.360 85.000 0.27% 30.000 45.000 PAR3 27.764 0.628 0.000 6.30% 10.000 20.000 25.000 381.000 381.750 -0.120 95.000 0.26% 30.000 45.000 PAR4 25.474 0.705 0.000 8.16% 8.333 18.333 23.333 343.000 348.665 0.142 91.667 0.29% 28.333 40.000 PAR5 25.115 0.578 0.000 6.62% 6.667 18.333 25.000 302.000 318.418 0.183 100.000 0.33% 30.000 41.667 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -7524.315 H0 Scaling Correction Factor 1.3517 for MLR Information Criteria Akaike (AIC) 15062.631 Bayesian (BIC) 15092.659 Sample-Size Adjusted BIC 15070.438 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 27.364 0.743 36.844 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 240.333 17.106 14.049 0.000 Residual Variances PAR1 170.116 18.782 9.057 0.000 PAR2 133.892 15.020 8.914 0.000 PAR3 123.246 17.122 7.198 0.000 PAR4 130.583 17.216 7.585 0.000 PAR5 165.304 19.707 8.388 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.616E-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 195.470 PAR2 0.000 194.291 PAR3 0.000 0.000 190.875 PAR4 0.000 0.000 0.000 174.333 PAR5 0.000 0.000 0.000 0.000 159.209 ALPHA P ________ 27.498 BETA P ________ P 0.000 PSI P ________ P 310.004 #Univariate LGCM - IPF parent: Female 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 539 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_Fem_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 PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 0.755 PAR2 0.566 0.688 PAR3 0.564 0.571 0.707 PAR4 0.512 0.494 0.532 0.636 PAR5 0.427 0.417 0.442 0.427 0.560 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 28.102 27.538 28.114 26.327 26.174 Covariances PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 404.737 PAR2 270.418 403.645 PAR3 241.970 281.812 390.943 PAR4 221.846 229.153 254.236 350.635 PAR5 194.445 209.371 210.572 200.018 338.662 Correlations PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1.000 PAR2 0.669 1.000 PAR3 0.608 0.709 1.000 PAR4 0.589 0.609 0.687 1.000 PAR5 0.525 0.566 0.579 0.580 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7507.859 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 28.384 0.472 0.000 7.13% 10.000 20.000 26.667 407.000 390.939 -0.526 85.000 0.25% 31.667 46.667 PAR2 27.277 0.595 0.000 6.20% 8.333 18.333 25.000 371.000 388.583 -0.360 85.000 0.27% 30.000 45.000 PAR3 27.764 0.628 0.000 6.30% 10.000 20.000 25.000 381.000 381.750 -0.120 95.000 0.26% 30.000 45.000 PAR4 25.474 0.705 0.000 8.16% 8.333 18.333 23.333 343.000 348.665 0.142 91.667 0.29% 28.333 40.000 PAR5 25.115 0.578 0.000 6.62% 6.667 18.333 25.000 302.000 318.418 0.183 100.000 0.33% 30.000 41.667 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -7516.438 H0 Scaling Correction Factor 1.2211 for MLR Information Criteria Akaike (AIC) 15052.876 Bayesian (BIC) 15095.773 Sample-Size Adjusted BIC 15064.030 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -17.475 6.648 -2.629 0.009 Means P 30.081 1.539 19.550 0.000 PS -0.297 0.136 -2.188 0.029 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 453.252 72.949 6.213 0.000 PS 1.229 0.633 1.941 0.052 Residual Variances PAR1 143.455 20.395 7.034 0.000 PAR2 130.314 14.634 8.905 0.000 PAR3 127.983 17.600 7.272 0.000 PAR4 130.213 17.083 7.622 0.000 PAR5 151.348 20.982 7.213 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.109E-02 (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 195.470 PAR2 0.000 194.291 PAR3 0.000 0.000 190.875 PAR4 0.000 0.000 0.000 174.333 PAR5 0.000 0.000 0.000 0.000 159.209 ALPHA P PS ________ ________ 29.789 -0.039 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 1119.247 PS 0.000 15.316 #Univariate LGCM - IPF parent: Female 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 539 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_Fem_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 PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 0.755 PAR2 0.566 0.688 PAR3 0.564 0.571 0.707 PAR4 0.512 0.494 0.532 0.636 PAR5 0.427 0.417 0.442 0.427 0.560 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ 28.102 27.538 28.114 26.327 26.174 Covariances PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 404.737 PAR2 270.418 403.645 PAR3 241.970 281.812 390.943 PAR4 221.846 229.153 254.236 350.635 PAR5 194.445 209.371 210.572 200.018 338.662 Correlations PAR1 PAR2 PAR3 PAR4 PAR5 ________ ________ ________ ________ ________ PAR1 1.000 PAR2 0.669 1.000 PAR3 0.608 0.709 1.000 PAR4 0.589 0.609 0.687 1.000 PAR5 0.525 0.566 0.579 0.580 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -7507.859 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 28.384 0.472 0.000 7.13% 10.000 20.000 26.667 407.000 390.939 -0.526 85.000 0.25% 31.667 46.667 PAR2 27.277 0.595 0.000 6.20% 8.333 18.333 25.000 371.000 388.583 -0.360 85.000 0.27% 30.000 45.000 PAR3 27.764 0.628 0.000 6.30% 10.000 20.000 25.000 381.000 381.750 -0.120 95.000 0.26% 30.000 45.000 PAR4 25.474 0.705 0.000 8.16% 8.333 18.333 23.333 343.000 348.665 0.142 91.667 0.29% 28.333 40.000 PAR5 25.115 0.578 0.000 6.62% 6.667 18.333 25.000 302.000 318.418 0.183 100.000 0.33% 30.000 41.667 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -7515.341 H0 Scaling Correction Factor 1.0640 for MLR Information Criteria Akaike (AIC) 15058.683 Bayesian (BIC) 15118.739 Sample-Size Adjusted BIC 15074.298 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -29.100 33.659 -0.865 0.387 PQ WITH P 0.452 1.385 0.326 0.744 PS -0.310 0.306 -1.011 0.312 Means P 30.233 2.812 10.753 0.000 PS -0.317 0.573 -0.553 0.580 PQ 0.000 0.029 0.010 0.992 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 444.994 172.352 2.582 0.010 PS 7.444 7.132 1.044 0.297 PQ 0.016 0.014 1.195 0.232 Residual Variances PAR1 137.228 21.321 6.436 0.000 PAR2 128.916 14.798 8.712 0.000 PAR3 125.178 17.750 7.052 0.000 PAR4 128.330 17.230 7.448 0.000 PAR5 148.404 19.561 7.587 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.217E-07 (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 195.470 PAR2 0.000 194.291 PAR3 0.000 0.000 190.875 PAR4 0.000 0.000 0.000 174.333 PAR5 0.000 0.000 0.000 0.000 159.209 ALPHA P PS PQ ________ ________ ________ 32.920 -0.899 0.053 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 3245.332 PS 0.000 310.976 PQ 0.000 0.000 2.178 #Univariate LGCM - IPF Work: Female 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 468 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_Fem_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 EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 0.641 EDU2 0.256 0.449 EDU3 0.184 0.214 0.353 EDU4 0.130 0.141 0.130 0.267 EDU5 0.081 0.062 0.060 0.051 0.165 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 ________ ________ ________ ________ ________ 31.103 30.228 31.297 30.414 32.065 Covariances EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 306.282 EDU2 188.637 280.034 EDU3 163.277 192.098 312.011 EDU4 166.698 169.255 140.246 331.883 EDU5 200.914 111.079 74.502 255.406 461.477 Correlations EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 1.000 EDU2 0.644 1.000 EDU3 0.528 0.650 1.000 EDU4 0.523 0.555 0.436 1.000 EDU5 0.534 0.309 0.196 0.653 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -3670.554 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 30.452 0.420 0.000 0.33% 14.444 24.444 29.881 300.000 297.496 -0.475 73.333 1.00% 34.444 45.556 EDU2 30.539 0.514 0.000 1.43% 15.556 23.333 28.333 210.000 279.674 -0.148 73.333 1.90% 33.333 44.444 EDU3 31.351 0.418 0.000 1.21% 15.556 23.333 31.111 165.000 295.178 -0.438 80.000 0.61% 35.556 47.778 EDU4 29.142 0.698 0.000 2.40% 14.444 22.222 27.778 125.000 329.242 0.116 78.571 0.80% 30.000 41.111 EDU5 30.091 0.789 1.111 1.30% 11.111 21.111 26.667 77.000 417.660 -0.281 78.571 1.30% 30.000 47.778 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -3678.039 H0 Scaling Correction Factor 1.5781 for MLR Information Criteria Akaike (AIC) 7370.078 Bayesian (BIC) 7399.118 Sample-Size Adjusted BIC 7376.901 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 30.795 0.749 41.090 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 176.316 17.533 10.056 0.000 Residual Variances EDU1 127.172 18.109 7.022 0.000 EDU2 90.149 17.064 5.283 0.000 EDU3 147.820 35.643 4.147 0.000 EDU4 172.795 51.276 3.370 0.001 EDU5 304.929 74.454 4.096 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.145E-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 148.748 EDU2 0.000 139.837 EDU3 0.000 0.000 147.589 EDU4 0.000 0.000 0.000 164.621 EDU5 0.000 0.000 0.000 0.000 208.830 ALPHA P ________ 30.990 BETA P ________ P 0.000 PSI P ________ P 277.394 #Univariate LGCM - IPF Work: Female 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 468 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_Fem_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 EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 0.641 EDU2 0.256 0.449 EDU3 0.184 0.214 0.353 EDU4 0.130 0.141 0.130 0.267 EDU5 0.081 0.062 0.060 0.051 0.165 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 ________ ________ ________ ________ ________ 31.103 30.228 31.297 30.414 32.065 Covariances EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 306.282 EDU2 188.637 280.034 EDU3 163.277 192.098 312.011 EDU4 166.698 169.255 140.246 331.883 EDU5 200.914 111.079 74.502 255.406 461.477 Correlations EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 1.000 EDU2 0.644 1.000 EDU3 0.528 0.650 1.000 EDU4 0.523 0.555 0.436 1.000 EDU5 0.534 0.309 0.196 0.653 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -3670.554 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 30.452 0.420 0.000 0.33% 14.444 24.444 29.881 300.000 297.496 -0.475 73.333 1.00% 34.444 45.556 EDU2 30.539 0.514 0.000 1.43% 15.556 23.333 28.333 210.000 279.674 -0.148 73.333 1.90% 33.333 44.444 EDU3 31.351 0.418 0.000 1.21% 15.556 23.333 31.111 165.000 295.178 -0.438 80.000 0.61% 35.556 47.778 EDU4 29.142 0.698 0.000 2.40% 14.444 22.222 27.778 125.000 329.242 0.116 78.571 0.80% 30.000 41.111 EDU5 30.091 0.789 1.111 1.30% 11.111 21.111 26.667 77.000 417.660 -0.281 78.571 1.30% 30.000 47.778 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -3678.285 H0 Scaling Correction Factor 1.4262 for MLR Information Criteria Akaike (AIC) 7376.570 Bayesian (BIC) 7418.055 Sample-Size Adjusted BIC 7386.317 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -4.467 15.963 -0.280 0.780 Means P 30.008 1.779 16.867 0.000 PS 0.098 0.197 0.500 0.617 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 220.223 136.447 1.614 0.107 PS 0.415 1.884 0.220 0.826 Residual Variances EDU1 123.167 20.922 5.887 0.000 EDU2 90.135 17.017 5.297 0.000 EDU3 148.501 36.129 4.110 0.000 EDU4 171.246 58.883 2.908 0.004 EDU5 302.254 84.720 3.568 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.415E-04 (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 148.748 EDU2 0.000 139.837 EDU3 0.000 0.000 147.589 EDU4 0.000 0.000 0.000 164.621 EDU5 0.000 0.000 0.000 0.000 208.830 ALPHA P PS ________ ________ 29.479 -0.689 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 797.009 PS 0.000 14.764 #Univariate LGCM - IPF Work: Female 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 468 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_Fem_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 EDU1 EDU2 EDU3 EDU4 EDU5 ________ ________ ________ ________ ________ EDU1 0.641 EDU2 0.256 0.449 EDU3 0.184 0.214 0.353 EDU4 0.130 0.141 0.130 0.267 EDU5 0.081 0.062 0.060 0.051 0.165 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 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 30.452 0.420 0.000 0.33% 14.444 24.444 29.881 300.000 297.496 -0.475 73.333 1.00% 34.444 45.556 EDU2 30.539 0.514 0.000 1.43% 15.556 23.333 28.333 210.000 279.674 -0.148 73.333 1.90% 33.333 44.444 EDU3 31.351 0.418 0.000 1.21% 15.556 23.333 31.111 165.000 295.178 -0.438 80.000 0.61% 35.556 47.778 EDU4 29.142 0.698 0.000 2.40% 14.444 22.222 27.778 125.000 329.242 0.116 78.571 0.80% 30.000 41.111 EDU5 30.091 0.789 1.111 1.30% 11.111 21.111 26.667 77.000 417.660 -0.281 78.571 1.30% 30.000 47.778 THE MODEL ESTIMATION DID NOT TERMINATE NORMALLY DUE TO AN ILL-CONDITIONED FISHER INFORMATION MATRIX. CHANGE YOUR MODEL AND/OR STARTING VALUES. THE MODEL ESTIMATION DID NOT TERMINATE NORMALLY DUE TO A NON-POSITIVE DEFINITE FISHER INFORMATION MATRIX. THIS MAY BE DUE TO THE STARTING VALUES BUT MAY ALSO BE AN INDICATION OF MODEL NONIDENTIFICATION. THE CONDITION NUMBER IS 0.271D-11. THE STANDARD ERRORS OF THE MODEL PARAMETER ESTIMATES COULD NOT BE COMPUTED. THIS IS OFTEN DUE TO THE STARTING VALUES BUT MAY ALSO BE AN INDICATION OF MODEL NONIDENTIFICATION. CHANGE YOUR MODEL AND/OR STARTING VALUES. PROBLEM INVOLVING THE FOLLOWING PARAMETER: Parameter 10, PS WITH P MODEL RESULTS Estimate PS WITH P 0.001 PQ WITH P -0.110 PS -0.405 Means P 29.347 PS 0.284 PQ -0.012 Intercepts EDU1 0.000 EDU2 0.000 EDU3 0.000 EDU4 0.000 EDU5 0.000 Variances P 131.330 PS 5.690 PQ 0.031 Residual Variances EDU1 117.074 EDU2 87.400 EDU3 148.241 EDU4 163.293 EDU5 267.086 MODEL COMMAND WITH FINAL ESTIMATES USED AS STARTING VALUES p ps pq | edu1 edu2 edu3 edu4 edu5 AT tsd1 tsd2 tsd3 tsd4 tsd5; ps WITH p*0.00136; pq WITH p*-0.11012; pq WITH ps*-0.40463; [ edu1@0 ]; [ edu2@0 ]; [ edu3@0 ]; [ edu4@0 ]; [ edu5@0 ]; [ p*29.34692 ]; [ ps*0.28386 ]; [ pq*-0.01168 ]; edu1*117.07352; edu2*87.39973; edu3*148.24072; edu4*163.29271; edu5*267.08582; p*131.32986; ps*5.68953; pq*0.03109; 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 148.748 EDU2 0.000 139.837 EDU3 0.000 0.000 147.589 EDU4 0.000 0.000 0.000 164.621 EDU5 0.000 0.000 0.000 0.000 208.830 ALPHA P PS PQ ________ ________ ________ 10.327 8.702 -0.988 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 5220.725 PS 0.000 784.233 PQ 0.000 0.000 10.083 #Univariate LGCM - IPF self care: Female 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 720 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_Fem_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 0.983 SLF2 0.851 0.865 SLF3 0.849 0.790 0.863 SLF4 0.756 0.696 0.728 0.767 SLF5 0.647 0.597 0.614 0.579 0.658 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 48.443 48.367 48.752 47.280 47.481 Covariances SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 363.707 SLF2 221.092 350.131 SLF3 208.780 225.893 335.809 SLF4 207.524 219.668 222.192 333.128 SLF5 205.573 215.249 210.957 225.397 361.257 Correlations SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1.000 SLF2 0.620 1.000 SLF3 0.597 0.659 1.000 SLF4 0.596 0.643 0.664 1.000 SLF5 0.567 0.605 0.606 0.650 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -12214.246 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 48.490 -0.193 0.000 0.14% 31.250 43.750 50.000 708.000 363.338 -0.525 91.667 0.14% 54.167 64.583 SLF2 48.006 -0.121 0.000 0.48% 31.250 43.750 47.917 623.000 348.685 -0.454 100.000 0.16% 54.167 64.583 SLF3 48.497 -0.192 0.000 0.16% 31.250 45.833 50.000 621.000 341.734 -0.516 93.750 0.48% 54.167 64.583 SLF4 47.107 -0.189 0.000 0.36% 31.250 43.750 47.917 552.000 335.026 -0.452 91.667 0.18% 52.083 62.500 SLF5 46.912 -0.126 0.000 0.21% 29.167 43.750 50.000 474.000 369.716 -0.598 95.833 0.42% 54.167 64.286 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 7 Loglikelihood H0 Value -12221.348 H0 Scaling Correction Factor 1.0555 for MLR Information Criteria Akaike (AIC) 24456.695 Bayesian (BIC) 24488.750 Sample-Size Adjusted BIC 24466.523 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Means P 48.131 0.592 81.253 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 216.991 11.886 18.256 0.000 Residual Variances SLF1 158.367 11.603 13.649 0.000 SLF2 123.914 9.441 13.124 0.000 SLF3 117.780 9.721 12.116 0.000 SLF4 113.966 8.599 13.254 0.000 SLF5 149.473 11.978 12.479 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.187E-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 181.669 SLF2 0.000 174.343 SLF3 0.000 0.000 170.867 SLF4 0.000 0.000 0.000 167.513 SLF5 0.000 0.000 0.000 0.000 184.858 ALPHA P ________ 48.210 BETA P ________ P 0.000 PSI P ________ P 253.032 #Univariate LGCM - IPF self care: Female 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 720 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_Fem_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 0.983 SLF2 0.851 0.865 SLF3 0.849 0.790 0.863 SLF4 0.756 0.696 0.728 0.767 SLF5 0.647 0.597 0.614 0.579 0.658 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 48.443 48.367 48.752 47.280 47.481 Covariances SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 363.707 SLF2 221.092 350.131 SLF3 208.780 225.893 335.809 SLF4 207.524 219.668 222.192 333.128 SLF5 205.573 215.249 210.957 225.397 361.257 Correlations SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1.000 SLF2 0.620 1.000 SLF3 0.597 0.659 1.000 SLF4 0.596 0.643 0.664 1.000 SLF5 0.567 0.605 0.606 0.650 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -12214.246 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 48.490 -0.193 0.000 0.14% 31.250 43.750 50.000 708.000 363.338 -0.525 91.667 0.14% 54.167 64.583 SLF2 48.006 -0.121 0.000 0.48% 31.250 43.750 47.917 623.000 348.685 -0.454 100.000 0.16% 54.167 64.583 SLF3 48.497 -0.192 0.000 0.16% 31.250 45.833 50.000 621.000 341.734 -0.516 93.750 0.48% 54.167 64.583 SLF4 47.107 -0.189 0.000 0.36% 31.250 43.750 47.917 552.000 335.026 -0.452 91.667 0.18% 52.083 62.500 SLF5 46.912 -0.126 0.000 0.21% 29.167 43.750 50.000 474.000 369.716 -0.598 95.833 0.42% 54.167 64.286 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 10 Loglikelihood H0 Value -12219.840 H0 Scaling Correction Factor 1.0479 for MLR Information Criteria Akaike (AIC) 24459.680 Bayesian (BIC) 24505.472 Sample-Size Adjusted BIC 24473.719 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -7.076 4.896 -1.445 0.148 Means P 48.648 1.084 44.861 0.000 PS -0.050 0.097 -0.512 0.608 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 284.502 54.005 5.268 0.000 PS 0.725 0.481 1.507 0.132 Residual Variances SLF1 146.282 13.876 10.542 0.000 SLF2 123.625 9.422 13.121 0.000 SLF3 119.067 9.848 12.091 0.000 SLF4 112.266 8.653 12.974 0.000 SLF5 136.359 13.787 9.891 0.000 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 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 181.669 SLF2 0.000 174.343 SLF3 0.000 0.000 170.867 SLF4 0.000 0.000 0.000 167.513 SLF5 0.000 0.000 0.000 0.000 184.858 ALPHA P PS ________ ________ 45.017 0.255 BETA P PS ________ ________ P 0.000 0.000 PS 0.000 0.000 PSI P PS ________ ________ P 715.969 PS 0.000 9.089 #Univariate LGCM - IPF self care: Female 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 720 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_Fem_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 0.983 SLF2 0.851 0.865 SLF3 0.849 0.790 0.863 SLF4 0.756 0.696 0.728 0.767 SLF5 0.647 0.597 0.614 0.579 0.658 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ 48.443 48.367 48.752 47.280 47.481 Covariances SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 363.707 SLF2 221.092 350.131 SLF3 208.780 225.893 335.809 SLF4 207.524 219.668 222.192 333.128 SLF5 205.573 215.249 210.957 225.397 361.257 Correlations SLF1 SLF2 SLF3 SLF4 SLF5 ________ ________ ________ ________ ________ SLF1 1.000 SLF2 0.620 1.000 SLF3 0.597 0.659 1.000 SLF4 0.596 0.643 0.664 1.000 SLF5 0.567 0.605 0.606 0.650 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -12214.246 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 48.490 -0.193 0.000 0.14% 31.250 43.750 50.000 708.000 363.338 -0.525 91.667 0.14% 54.167 64.583 SLF2 48.006 -0.121 0.000 0.48% 31.250 43.750 47.917 623.000 348.685 -0.454 100.000 0.16% 54.167 64.583 SLF3 48.497 -0.192 0.000 0.16% 31.250 45.833 50.000 621.000 341.734 -0.516 93.750 0.48% 54.167 64.583 SLF4 47.107 -0.189 0.000 0.36% 31.250 43.750 47.917 552.000 335.026 -0.452 91.667 0.18% 52.083 62.500 SLF5 46.912 -0.126 0.000 0.21% 29.167 43.750 50.000 474.000 369.716 -0.598 95.833 0.42% 54.167 64.286 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 14 Loglikelihood H0 Value -12215.023 H0 Scaling Correction Factor 0.9176 for MLR Information Criteria Akaike (AIC) 24458.046 Bayesian (BIC) 24522.155 Sample-Size Adjusted BIC 24477.701 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value PS WITH P -9.745 13.813 -0.705 0.481 PQ WITH P 0.374 0.792 0.473 0.636 PS -0.228 0.203 -1.127 0.260 Means P 43.917 1.889 23.254 0.000 PS 1.060 0.393 2.697 0.007 PQ -0.059 0.021 -2.851 0.004 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 246.872 75.032 3.290 0.001 PS 4.000 3.398 1.177 0.239 PQ 0.015 0.012 1.249 0.212 Residual Variances SLF1 145.946 12.515 11.661 0.000 SLF2 122.171 9.612 12.710 0.000 SLF3 117.596 9.863 11.923 0.000 SLF4 112.259 8.639 12.994 0.000 SLF5 124.847 13.650 9.146 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.733E-08 (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 181.669 SLF2 0.000 174.343 SLF3 0.000 0.000 170.867 SLF4 0.000 0.000 0.000 167.513 SLF5 0.000 0.000 0.000 0.000 184.858 ALPHA P PS PQ ________ ________ ________ 46.073 -1.129 0.201 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 2940.103 PS 0.000 301.299 PQ 0.000 0.000 2.306