Mplus VERSION 6.1 MUTHEN & MUTHEN 10/18/2010 11:28 AM INPUT INSTRUCTIONS Title: Data: File = StarD Ratings 1-23-09.dat; Variable: Names = ID DATE_0 CSOIN_0 CMNIN_0 CEMIN_0 CHYSM_0 CMDSD_0 CAPDC_0 CAPIN_0 CWTDC_0 CWTIN_0 CCNTR_0 CVWSF_0 CSUIC_0 CINTR_0 CENGY_0 CSLOW_0 CAGIT_0 y0 DATE_2 CSOIN_2 CMNIN_2 CEMIN_2 CHYSM_2 CMDSD_2 CAPDC_2 CAPIN_2 CWTDC_2 CWTIN_2 CCNTR_2 CVWSF_2 CSUIC_2 CINTR_2 CENGY_2 CSLOW_2 CAGIT_2 y1 DATE_4 CSOIN_4 CMNIN_4 CEMIN_4 CHYSM_4 CMDSD_4 CAPDC_4 CAPIN_4 CWTDC_4 CWTIN_4 CCNTR_4 CVWSF_4 CSUIC_4 CINTR_4 CENGY_4 CSLOW_4 CAGIT_4 y2 DATE_6 SOIN_6 CMNIN_6 CEMIN_6 CHYSM_6 CMDSD_6 CAPDC_6 CAPIN_6 CWTDC_6 CWTIN_6 CCNTR_6 CVWSF_6 CSUIC_6 CINTR_6 CENGY_6 CSLOW_6 CAGIT_6 y3 DATE_9 CSOIN_9 CMNIN_9 CEMIN_9 CHYSM_9 CMDSD_9 CAPDC_9 CAPIN_9 CWTDC_9 CWTIN_9 CCNTR_9 CVWSF_9 CSUIC_9 CINTR_9 CENGY_9 CSLOW_9 CAGIT_9 y4 DATE_12 CSOIN_12 CMNIN_12 CEMIN_12 CHYSM_12 CMDSD_12 CAPDC_12 CAPIN_12 CWTDC_12 CWTIN_12 CCNTR_12 CVWSF_12 CSUIC_12 CINTR_12 CENGY_12 CSLOW_12 CAGIT_12 y5 DATE_14 CSOIN_14 CMNIN_14 CEMIN_14 CHYSM_14 CMDSD_14 CAPDC_14 CAPIN_14 CWTDC_14 CWTIN_14 CCNTR_14 CVWSF_14 CSUIC_14 CINTR_14 CENGY_14 CSLOW_14 CAGIT_14 y6 !Self-Ratings. SSOIN_0 SMNIN_0 SEMIN_0 SHYSM_0 SMDSD_0 SAPDC_0 SAPIN_0 SWTDC_0 SWTIN_0 SCNTR_0 SVWSF_0 SSUIC_0 SINTR_0 SENGY_0 SSLOW_0 SAGIT_0 QSTOT_0 SSOIN_2 SMNIN_2 SEMIN_2 SHYSM_2 SMDSD_2 SAPDC_2 SAPIN_2 SWTDC_2 SWTIN_2 SCNTR_2 SVWSF_2 SSUIC_2 SINTR_2 SENGY_2 SSLOW_2 SAGIT_2 QSTOT_2 SSOIN_4 SMNIN_4 SEMIN_4 SHYSM_4 SMDSD_4 SAPDC_4 SAPIN_4 SWTDC_4 SWTIN_4 SCNTR_4 SVWSF_4 SSUIC_4 SINTR_4 SENGY_4 SSLOW_4 SAGIT_4 QSTOT_4 SSOIN_6 SMNIN_6 SEMIN_6 SHYSM_6 SMDSD_6 SAPDC_6 SAPIN_6 SWTDC_6 SWTIN_6 SCNTR_6 SVWSF_6 SSUIC_6 SINTR_6 SENGY_6 SSLOW_6 SAGIT_6 QSTOT_6 SSOIN_9 SMNIN_9 SEMIN_9 SHYSM_9 SMDSD_9 SAPDC_9 SAPIN_9 SWTDC_9 SWTIN_9 SCNTR_9 SVWSF_9 SSUIC_9 SINTR_9 SENGY_9 SSLOW_9 SAGIT_9 QSTOT_9 SSOIN_12 SMNIN_12 SEMIN_12 SHYSM_12 SMDSD_12 SAPDC_12 SAPIN_12 SWTDC_12 SWTIN_12 SCNTR_12 SVWSF_12 SSUIC_12 SINTR_12 SENGY_12 SSLOW_12 SAGIT_12 QSTOT_12 SSOIN_14 SMNIN_14 SEMIN_14 SHYSM_14 SMDSD_14 SAPDC_14 SAPIN_14 SWTDC_14 SWTIN_14 SCNTR_14 SVWSF_14 SSUIC_14 SINTR_14 SENGY_14 SSLOW_14 SAGIT_14 QSTOT_14; Missing = all (-9999); usev = y0 y1 y2 y3 y4 y5 d1 d2 d3 d4 d5; classes = c(1); Data missing: names = y0 y1 y2 y3 y4 y5; type = ddropout; binary = d1-d5; Analysis: type = mixture; process = 4(starts); interactive = control.dat; Model: %overall% i s q | y0@0 y1@.2 y2@.4 y3@.6 y4@.9 y5@1.2; i-q on d4-d5; i on d1 d2 d3; s on d3; s on d1 (1); s on d2 (1); q on d1 (2); q on d2 (2); q on d3 (2); Plot: type = plot3; series = y0-y5(s); Output: tech1 sampstat residual standardized; INPUT READING TERMINATED NORMALLY SUMMARY OF ANALYSIS Number of groups 1 Number of observations 4041 Number of dependent variables 6 Number of independent variables 5 Number of continuous latent variables 3 Number of categorical latent variables 1 Observed dependent variables Continuous Y0 Y1 Y2 Y3 Y4 Y5 Observed independent variables D1 D2 D3 D4 D5 Continuous latent variables I S Q Categorical latent variables C Estimator MLR Information matrix OBSERVED Optimization Specifications for the Quasi-Newton Algorithm for Continuous Outcomes Maximum number of iterations 100 Convergence criterion 0.100D-05 Optimization Specifications for the EM Algorithm Maximum number of iterations 500 Convergence criteria Loglikelihood change 0.100D-06 Relative loglikelihood change 0.100D-06 Derivative 0.100D-05 Optimization Specifications for the M step of the EM Algorithm for Categorical Latent variables Number of M step iterations 1 M step convergence criterion 0.100D-05 Basis for M step termination ITERATION Optimization Specifications for the M step of the EM Algorithm for Censored, Binary or Ordered Categorical (Ordinal), Unordered Categorical (Nominal) and Count Outcomes Number of M step iterations 1 M step convergence criterion 0.100D-05 Basis for M step termination ITERATION Maximum value for logit thresholds 15 Minimum value for logit thresholds -15 Minimum expected cell size for chi-square 0.100D-01 Maximum number of iterations for H1 2000 Convergence criterion for H1 0.100D-03 Optimization algorithm EMA Input data file(s) StarD Ratings 1-23-09.dat Input data format FREE SUMMARY OF DATA Number of missing data patterns 34 Number of y missing data patterns 34 Number of u missing data patterns 0 COVARIANCE COVERAGE OF DATA Minimum covariance coverage value 0.100 PROPORTION OF DATA PRESENT FOR Y Covariance Coverage Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ Y0 1.000 Y1 0.790 0.790 Y2 0.693 0.607 0.694 Y3 0.677 0.603 0.564 0.677 Y4 0.571 0.508 0.490 0.511 0.571 Y5 0.385 0.349 0.333 0.343 0.328 D1 1.000 0.790 0.694 0.677 0.571 D2 1.000 0.790 0.694 0.677 0.571 D3 1.000 0.790 0.694 0.677 0.571 D4 1.000 0.790 0.694 0.677 0.571 D5 1.000 0.790 0.694 0.677 0.571 Covariance Coverage Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ Y5 0.385 D1 0.385 1.000 D2 0.385 1.000 1.000 D3 0.385 1.000 1.000 1.000 D4 0.385 1.000 1.000 1.000 1.000 D5 0.385 1.000 1.000 1.000 1.000 Covariance Coverage D5 ________ D5 1.000 SAMPLE STATISTICS ESTIMATED SAMPLE STATISTICS Means Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ 1 16.405 12.215 10.651 9.319 8.217 Means Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ 1 6.999 0.104 0.074 0.074 0.120 Means D5 ________ 1 0.243 Covariances Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ Y0 11.660 Y1 8.098 20.395 Y2 7.342 15.050 23.956 Y3 6.326 13.306 17.414 24.836 Y4 5.810 12.453 15.894 18.194 26.350 Y5 5.523 12.282 15.060 17.075 20.330 D1 0.006 -0.009 -0.004 -0.005 -0.003 D2 0.007 0.062 -0.003 -0.003 -0.002 D3 0.024 0.014 0.096 0.002 0.002 D4 0.033 0.083 0.122 0.222 0.005 D5 -0.006 0.015 0.022 0.043 0.189 Covariances Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ Y5 27.998 D1 -0.001 0.093 D2 -0.001 -0.008 0.069 D3 0.002 -0.008 -0.006 0.069 D4 0.004 -0.012 -0.009 -0.009 0.105 D5 0.001 -0.025 -0.018 -0.018 -0.029 Covariances D5 ________ D5 0.184 Correlations Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ Y0 1.000 Y1 0.525 1.000 Y2 0.439 0.681 1.000 Y3 0.372 0.591 0.714 1.000 Y4 0.331 0.537 0.633 0.711 1.000 Y5 0.306 0.514 0.582 0.648 0.748 D1 0.006 -0.007 -0.003 -0.003 -0.002 D2 0.008 0.052 -0.002 -0.002 -0.002 D3 0.027 0.011 0.074 0.001 0.001 D4 0.030 0.057 0.077 0.137 0.003 D5 -0.004 0.008 0.011 0.020 0.086 Correlations Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ Y5 1.000 D1 -0.001 1.000 D2 -0.001 -0.096 1.000 D3 0.001 -0.097 -0.080 1.000 D4 0.002 -0.126 -0.104 -0.105 1.000 D5 0.001 -0.193 -0.160 -0.161 -0.209 Correlations D5 ________ D5 1.000 MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -49189.312 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 27 Loglikelihood H0 Value -44946.328 H0 Scaling Correction Factor 1.088 for MLR Information Criteria Akaike (AIC) 89946.656 Bayesian (BIC) 90116.871 Sample-Size Adjusted BIC 90031.077 (n* = (n + 2) / 24) FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES BASED ON THE ESTIMATED MODEL Latent Classes 1 4041.00000 1.00000 FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS BASED ON ESTIMATED POSTERIOR PROBABILITIES Latent Classes 1 4041.00000 1.00000 CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP Class Counts and Proportions Latent Classes 1 4041 1.00000 Average Latent Class Probabilities for Most Likely Latent Class Membership (Row) by Latent Class (Column) 1 1 1.000 MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Latent Class 1 I | Y0 1.000 0.000 999.000 999.000 Y1 1.000 0.000 999.000 999.000 Y2 1.000 0.000 999.000 999.000 Y3 1.000 0.000 999.000 999.000 Y4 1.000 0.000 999.000 999.000 Y5 1.000 0.000 999.000 999.000 S | Y0 0.000 0.000 999.000 999.000 Y1 0.200 0.000 999.000 999.000 Y2 0.400 0.000 999.000 999.000 Y3 0.600 0.000 999.000 999.000 Y4 0.900 0.000 999.000 999.000 Y5 1.200 0.000 999.000 999.000 Q | Y0 0.000 0.000 999.000 999.000 Y1 0.040 0.000 999.000 999.000 Y2 0.160 0.000 999.000 999.000 Y3 0.360 0.000 999.000 999.000 Y4 0.810 0.000 999.000 999.000 Y5 1.440 0.000 999.000 999.000 I ON D4 0.710 0.174 4.079 0.000 D5 0.319 0.139 2.293 0.022 D1 0.528 0.198 2.668 0.008 D2 0.571 0.216 2.643 0.008 D3 0.797 0.224 3.562 0.000 S ON D4 -3.813 1.105 -3.451 0.001 D5 -1.468 0.598 -2.453 0.014 D3 -14.089 1.359 -10.365 0.000 D1 -9.552 1.437 -6.647 0.000 D2 -9.552 1.437 -6.647 0.000 Q ON D4 12.041 1.632 7.377 0.000 D5 3.753 0.553 6.788 0.000 D1 40.602 2.489 16.315 0.000 D2 40.602 2.489 16.315 0.000 D3 40.602 2.489 16.315 0.000 S WITH I -0.038 1.325 -0.029 0.977 Q WITH I -1.485 0.954 -1.556 0.120 S -59.561 4.329 -13.759 0.000 Intercepts Y0 0.000 0.000 999.000 999.000 Y1 0.000 0.000 999.000 999.000 Y2 0.000 0.000 999.000 999.000 Y3 0.000 0.000 999.000 999.000 Y4 0.000 0.000 999.000 999.000 Y5 0.000 0.000 999.000 999.000 I 15.934 0.089 179.236 0.000 S -17.574 0.321 -54.766 0.000 Q 8.572 0.251 34.153 0.000 Residual Variances Y0 4.339 0.371 11.687 0.000 Y1 8.974 0.290 30.920 0.000 Y2 7.160 0.331 21.632 0.000 Y3 6.131 0.316 19.426 0.000 Y4 7.426 0.433 17.150 0.000 Y5 4.965 0.840 5.908 0.000 I 7.650 0.372 20.557 0.000 S 90.641 5.646 16.053 0.000 Q 44.772 3.625 12.351 0.000 STANDARDIZED MODEL RESULTS STDYX Standardization Two-Tailed Estimate S.E. Est./S.E. P-Value Latent Class 1 I | Y0 0.800 0.018 44.051 0.000 Y1 0.633 0.014 44.718 0.000 Y2 0.571 0.015 38.889 0.000 Y3 0.448 0.016 27.193 0.000 Y4 0.249 0.014 17.937 0.000 Y5 0.142 0.009 15.708 0.000 S | Y0 0.000 0.000 999.000 999.000 Y1 0.480 0.015 31.623 0.000 Y2 0.866 0.030 28.618 0.000 Y3 1.020 0.043 23.867 0.000 Y4 0.851 0.045 18.885 0.000 Y5 0.644 0.037 17.548 0.000 Q | Y0 0.000 0.000 999.000 999.000 Y1 0.164 0.009 17.716 0.000 Y2 0.590 0.033 17.927 0.000 Y3 1.043 0.049 21.488 0.000 Y4 1.304 0.040 32.383 0.000 Y5 1.317 0.030 43.435 0.000 I ON D4 0.083 0.021 4.041 0.000 D5 0.049 0.022 2.285 0.022 D1 0.058 0.022 2.651 0.008 D2 0.054 0.020 2.629 0.009 D3 0.075 0.021 3.532 0.000 S ON D4 -0.117 0.034 -3.444 0.001 D5 -0.060 0.025 -2.436 0.015 D3 -0.351 0.030 -11.574 0.000 D1 -0.276 0.038 -7.348 0.000 D2 -0.237 0.032 -7.348 0.000 Q ON D4 0.218 0.032 6.801 0.000 D5 0.090 0.014 6.241 0.000 D1 0.690 0.010 65.812 0.000 D2 0.592 0.009 62.923 0.000 D3 0.593 0.009 62.966 0.000 S WITH I -0.001 0.050 -0.029 0.977 Q WITH I -0.080 0.054 -1.477 0.140 S -0.935 0.007 -133.098 0.000 Intercepts Y0 0.000 0.000 999.000 999.000 Y1 0.000 0.000 999.000 999.000 Y2 0.000 0.000 999.000 999.000 Y3 0.000 0.000 999.000 999.000 Y4 0.000 0.000 999.000 999.000 Y5 0.000 0.000 999.000 999.000 I 5.730 0.133 42.954 0.000 S -1.666 0.061 -27.384 0.000 Q 0.477 0.030 15.733 0.000 Residual Variances Y0 0.359 0.029 12.356 0.000 Y1 0.466 0.011 40.967 0.000 Y2 0.302 0.013 22.543 0.000 Y3 0.159 0.011 13.909 0.000 Y4 0.060 0.007 8.716 0.000 Y5 0.013 0.003 4.890 0.000 I 0.989 0.004 238.764 0.000 S 0.815 0.034 23.737 0.000 Q 0.139 0.017 7.994 0.000 STDY Standardization Two-Tailed Estimate S.E. Est./S.E. P-Value Latent Class 1 I | Y0 0.800 0.018 44.051 0.000 Y1 0.633 0.014 44.718 0.000 Y2 0.571 0.015 38.889 0.000 Y3 0.448 0.016 27.193 0.000 Y4 0.249 0.014 17.937 0.000 Y5 0.142 0.009 15.708 0.000 S | Y0 0.000 0.000 999.000 999.000 Y1 0.480 0.015 31.623 0.000 Y2 0.866 0.030 28.618 0.000 Y3 1.020 0.043 23.867 0.000 Y4 0.851 0.045 18.885 0.000 Y5 0.644 0.037 17.548 0.000 Q | Y0 0.000 0.000 999.000 999.000 Y1 0.164 0.009 17.716 0.000 Y2 0.590 0.033 17.927 0.000 Y3 1.043 0.049 21.488 0.000 Y4 1.304 0.040 32.383 0.000 Y5 1.317 0.030 43.435 0.000 I ON D4 0.255 0.063 4.045 0.000 D5 0.115 0.050 2.286 0.022 D1 0.190 0.072 2.652 0.008 D2 0.205 0.078 2.630 0.009 D3 0.287 0.081 3.534 0.000 S ON D4 -0.362 0.105 -3.446 0.001 D5 -0.139 0.057 -2.437 0.015 D3 -1.336 0.115 -11.656 0.000 D1 -0.906 0.123 -7.371 0.000 D2 -0.906 0.123 -7.371 0.000 Q ON D4 0.670 0.098 6.821 0.000 D5 0.209 0.033 6.253 0.000 D1 2.260 0.030 75.196 0.000 D2 2.260 0.030 75.196 0.000 D3 2.260 0.030 75.196 0.000 S WITH I -0.001 0.050 -0.029 0.977 Q WITH I -0.080 0.054 -1.477 0.140 S -0.935 0.007 -133.098 0.000 Intercepts Y0 0.000 0.000 999.000 999.000 Y1 0.000 0.000 999.000 999.000 Y2 0.000 0.000 999.000 999.000 Y3 0.000 0.000 999.000 999.000 Y4 0.000 0.000 999.000 999.000 Y5 0.000 0.000 999.000 999.000 I 5.730 0.133 42.954 0.000 S -1.666 0.061 -27.384 0.000 Q 0.477 0.030 15.733 0.000 Residual Variances Y0 0.359 0.029 12.356 0.000 Y1 0.466 0.011 40.967 0.000 Y2 0.302 0.013 22.543 0.000 Y3 0.159 0.011 13.909 0.000 Y4 0.060 0.007 8.716 0.000 Y5 0.013 0.003 4.890 0.000 I 0.989 0.004 238.764 0.000 S 0.815 0.034 23.737 0.000 Q 0.139 0.017 7.994 0.000 STD Standardization Two-Tailed Estimate S.E. Est./S.E. P-Value Latent Class 1 I | Y0 2.781 0.066 41.973 0.000 Y1 2.781 0.066 41.973 0.000 Y2 2.781 0.066 41.973 0.000 Y3 2.781 0.066 41.973 0.000 Y4 2.781 0.066 41.973 0.000 Y5 2.781 0.066 41.973 0.000 S | Y0 0.000 0.000 999.000 999.000 Y1 2.109 0.068 31.138 0.000 Y2 4.219 0.135 31.138 0.000 Y3 6.328 0.203 31.138 0.000 Y4 9.492 0.305 31.138 0.000 Y5 12.656 0.406 31.138 0.000 Q | Y0 0.000 0.000 999.000 999.000 Y1 0.719 0.040 17.803 0.000 Y2 2.875 0.161 17.803 0.000 Y3 6.468 0.363 17.803 0.000 Y4 14.553 0.817 17.803 0.000 Y5 25.873 1.453 17.803 0.000 I ON D4 0.255 0.063 4.045 0.000 D5 0.115 0.050 2.286 0.022 D1 0.190 0.072 2.652 0.008 D2 0.205 0.078 2.630 0.009 D3 0.287 0.081 3.534 0.000 S ON D4 -0.362 0.105 -3.446 0.001 D5 -0.139 0.057 -2.437 0.015 D3 -1.336 0.115 -11.656 0.000 D1 -0.906 0.123 -7.371 0.000 D2 -0.906 0.123 -7.371 0.000 Q ON D4 0.670 0.098 6.821 0.000 D5 0.209 0.033 6.253 0.000 D1 2.260 0.030 75.196 0.000 D2 2.260 0.030 75.196 0.000 D3 2.260 0.030 75.196 0.000 S WITH I -0.001 0.050 -0.029 0.977 Q WITH I -0.080 0.054 -1.477 0.140 S -0.935 0.007 -133.098 0.000 Intercepts Y0 0.000 0.000 999.000 999.000 Y1 0.000 0.000 999.000 999.000 Y2 0.000 0.000 999.000 999.000 Y3 0.000 0.000 999.000 999.000 Y4 0.000 0.000 999.000 999.000 Y5 0.000 0.000 999.000 999.000 I 5.730 0.133 42.954 0.000 S -1.666 0.061 -27.384 0.000 Q 0.477 0.030 15.733 0.000 Residual Variances Y0 4.339 0.371 11.687 0.000 Y1 8.974 0.290 30.920 0.000 Y2 7.160 0.331 21.632 0.000 Y3 6.131 0.316 19.426 0.000 Y4 7.426 0.433 17.150 0.000 Y5 4.965 0.840 5.908 0.000 I 0.989 0.004 238.764 0.000 S 0.815 0.034 23.737 0.000 Q 0.139 0.017 7.994 0.000 R-SQUARE Class 1 Observed Two-Tailed Variable Estimate S.E. Est./S.E. P-Value Y0 0.641 0.029 22.025 0.000 Y1 0.534 0.011 47.028 0.000 Y2 0.698 0.013 52.155 0.000 Y3 0.841 0.011 73.381 0.000 Y4 0.940 0.007 137.408 0.000 Y5 0.987 0.003 375.131 0.000 Latent Two-Tailed Variable Estimate S.E. Est./S.E. P-Value I 0.011 0.004 2.613 0.009 S 0.185 0.034 5.393 0.000 Q 0.861 0.017 49.648 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.114E-04 (ratio of smallest to largest eigenvalue) RESIDUAL OUTPUT ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR CLASS 1 Model Estimated Means Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ 1 16.253 12.873 11.186 11.194 14.382 Model Estimated Means Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ 1 21.381 0.104 0.074 0.074 0.120 Model Estimated Means D5 ________ 1 0.243 Residuals for Means Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ 1 0.152 -0.746 -0.576 -1.918 -6.196 Residuals for Means Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ 1 -14.395 0.000 0.000 0.000 0.000 Residuals for Means D5 ________ 1 0.000 Model Estimated Covariances Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ Y0 12.073 Y1 7.600 19.275 Y2 7.638 12.079 23.726 Y3 7.850 12.934 21.098 38.474 Y4 8.492 12.483 27.982 54.988 124.500 Y5 9.524 9.955 34.968 84.564 205.051 D1 0.022 0.014 0.238 0.696 1.819 D2 0.019 0.013 0.173 0.499 1.298 D3 0.036 -0.038 0.056 0.316 1.019 D4 0.047 0.038 0.024 0.005 -0.035 D5 0.000 0.016 -0.141 -0.469 -1.285 Model Estimated Covariances Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ Y5 385.814 D1 3.465 0.093 D2 2.470 -0.008 0.069 D3 2.098 -0.008 -0.006 0.069 D4 -0.086 -0.012 -0.009 -0.009 0.105 D5 -2.489 -0.025 -0.018 -0.018 -0.029 Model Estimated Covariances D5 ________ D5 0.184 Residuals for Covariances Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ Y0 -0.412 Y1 -0.414 0.880 Y2 -0.931 -0.853 -0.075 Y3 -2.802 -3.535 -8.064 -14.173 Y4 -4.419 -5.138 -16.699 -43.378 -99.279 Y5 -6.461 -5.695 -29.229 -79.437 -196.549 D1 -0.015 -1.274 -1.341 -1.660 -2.669 D2 -0.011 0.312 -0.958 -1.185 -1.904 D3 -0.011 0.022 0.435 -1.007 -1.629 D4 -0.012 0.179 0.157 0.861 -0.946 D5 -0.012 0.208 0.658 1.195 3.123 Residuals for Covariances Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ Y5 -361.796 D1 -4.191 0.000 D2 -2.987 0.000 0.000 D3 -2.618 0.000 0.000 0.000 D4 -0.751 0.000 0.000 0.000 0.000 D5 0.789 0.000 0.000 0.000 0.000 Residuals for Covariances D5 ________ D5 0.000 TECHNICAL 1 OUTPUT PARAMETER SPECIFICATION FOR LATENT CLASS 1 NU Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ 1 0 0 0 0 0 NU Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ 1 0 0 0 0 0 NU D5 ________ 1 0 LAMBDA I S Q D1 D2 ________ ________ ________ ________ ________ Y0 0 0 0 0 0 Y1 0 0 0 0 0 Y2 0 0 0 0 0 Y3 0 0 0 0 0 Y4 0 0 0 0 0 Y5 0 0 0 0 0 D1 0 0 0 0 0 D2 0 0 0 0 0 D3 0 0 0 0 0 D4 0 0 0 0 0 D5 0 0 0 0 0 LAMBDA D3 D4 D5 ________ ________ ________ Y0 0 0 0 Y1 0 0 0 Y2 0 0 0 Y3 0 0 0 Y4 0 0 0 Y5 0 0 0 D1 0 0 0 D2 0 0 0 D3 0 0 0 D4 0 0 0 D5 0 0 0 THETA Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ Y0 1 Y1 0 2 Y2 0 0 3 Y3 0 0 0 4 Y4 0 0 0 0 5 Y5 0 0 0 0 0 D1 0 0 0 0 0 D2 0 0 0 0 0 D3 0 0 0 0 0 D4 0 0 0 0 0 D5 0 0 0 0 0 THETA Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ Y5 6 D1 0 0 D2 0 0 0 D3 0 0 0 0 D4 0 0 0 0 0 D5 0 0 0 0 0 THETA D5 ________ D5 0 ALPHA I S Q D1 D2 ________ ________ ________ ________ ________ 1 7 8 9 0 0 ALPHA D3 D4 D5 ________ ________ ________ 1 0 0 0 BETA I S Q D1 D2 ________ ________ ________ ________ ________ I 0 0 0 10 11 S 0 0 0 15 15 Q 0 0 0 19 19 D1 0 0 0 0 0 D2 0 0 0 0 0 D3 0 0 0 0 0 D4 0 0 0 0 0 D5 0 0 0 0 0 BETA D3 D4 D5 ________ ________ ________ I 12 13 14 S 16 17 18 Q 19 20 21 D1 0 0 0 D2 0 0 0 D3 0 0 0 D4 0 0 0 D5 0 0 0 PSI I S Q D1 D2 ________ ________ ________ ________ ________ I 22 S 23 24 Q 25 26 27 D1 0 0 0 0 D2 0 0 0 0 0 D3 0 0 0 0 0 D4 0 0 0 0 0 D5 0 0 0 0 0 PSI D3 D4 D5 ________ ________ ________ D3 0 D4 0 0 D5 0 0 0 PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART ALPHA(C) C#1 ________ 1 0 GAMMA(C) D1 D2 D3 D4 D5 ________ ________ ________ ________ ________ C#1 0 0 0 0 0 STARTING VALUES FOR LATENT CLASS 1 NU Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ 1 0.000 0.000 0.000 0.000 0.000 NU Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ 1 0.000 0.000 0.000 0.000 0.000 NU D5 ________ 1 0.000 LAMBDA I S Q D1 D2 ________ ________ ________ ________ ________ Y0 1.000 0.000 0.000 0.000 0.000 Y1 1.000 0.200 0.040 0.000 0.000 Y2 1.000 0.400 0.160 0.000 0.000 Y3 1.000 0.600 0.360 0.000 0.000 Y4 1.000 0.900 0.810 0.000 0.000 Y5 1.000 1.200 1.440 0.000 0.000 D1 0.000 0.000 0.000 1.000 0.000 D2 0.000 0.000 0.000 0.000 1.000 D3 0.000 0.000 0.000 0.000 0.000 D4 0.000 0.000 0.000 0.000 0.000 D5 0.000 0.000 0.000 0.000 0.000 LAMBDA D3 D4 D5 ________ ________ ________ Y0 0.000 0.000 0.000 Y1 0.000 0.000 0.000 Y2 0.000 0.000 0.000 Y3 0.000 0.000 0.000 Y4 0.000 0.000 0.000 Y5 0.000 0.000 0.000 D1 0.000 0.000 0.000 D2 0.000 0.000 0.000 D3 1.000 0.000 0.000 D4 0.000 1.000 0.000 D5 0.000 0.000 1.000 THETA Y0 Y1 Y2 Y3 Y4 ________ ________ ________ ________ ________ Y0 5.832 Y1 0.000 10.081 Y2 0.000 0.000 11.830 Y3 0.000 0.000 0.000 12.155 Y4 0.000 0.000 0.000 0.000 12.616 Y5 0.000 0.000 0.000 0.000 0.000 D1 0.000 0.000 0.000 0.000 0.000 D2 0.000 0.000 0.000 0.000 0.000 D3 0.000 0.000 0.000 0.000 0.000 D4 0.000 0.000 0.000 0.000 0.000 D5 0.000 0.000 0.000 0.000 0.000 THETA Y5 D1 D2 D3 D4 ________ ________ ________ ________ ________ Y5 12.016 D1 0.000 0.000 D2 0.000 0.000 0.000 D3 0.000 0.000 0.000 0.000 D4 0.000 0.000 0.000 0.000 0.000 D5 0.000 0.000 0.000 0.000 0.000 THETA D5 ________ D5 0.000 ALPHA I S Q D1 D2 ________ ________ ________ ________ ________ 1 15.896 -17.988 10.275 0.000 0.000 ALPHA D3 D4 D5 ________ ________ ________ 1 0.000 0.000 0.000 BETA I S Q D1 D2 ________ ________ ________ ________ ________ I 0.000 0.000 0.000 0.000 0.000 S 0.000 0.000 0.000 0.000 0.000 Q 0.000 0.000 0.000 0.000 0.000 D1 0.000 0.000 0.000 0.000 0.000 D2 0.000 0.000 0.000 0.000 0.000 D3 0.000 0.000 0.000 0.000 0.000 D4 0.000 0.000 0.000 0.000 0.000 D5 0.000 0.000 0.000 0.000 0.000 BETA D3 D4 D5 ________ ________ ________ I 0.000 0.000 0.000 S 0.000 0.000 0.000 Q 0.000 0.000 0.000 D1 0.000 0.000 0.000 D2 0.000 0.000 0.000 D3 0.000 0.000 0.000 D4 0.000 0.000 0.000 D5 0.000 0.000 0.000 PSI I S Q D1 D2 ________ ________ ________ ________ ________ I 11.807 S 0.000 203.468 Q 0.000 0.000 233.785 D1 0.000 0.000 0.000 0.047 D2 0.000 0.000 0.000 0.000 0.034 D3 0.000 0.000 0.000 0.000 0.000 D4 0.000 0.000 0.000 0.000 0.000 D5 0.000 0.000 0.000 0.000 0.000 PSI D3 D4 D5 ________ ________ ________ D3 0.034 D4 0.000 0.053 D5 0.000 0.000 0.092 STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART ALPHA(C) C#1 ________ 1 0.000 GAMMA(C) D1 D2 D3 D4 D5 ________ ________ ________ ________ ________ C#1 0.000 0.000 0.000 0.000 0.000 SAMPLE STATISTICS FOR ESTIMATED FACTOR SCORES SAMPLE STATISTICS Means I S Q C_I C_S ________ ________ ________ ________ ________ 1 16.253 -21.136 21.175 16.253 -21.136 Means C_Q ________ 1 21.175 Covariances I S Q C_I C_S ________ ________ ________ ________ ________ I 5.500 S 3.030 67.999 Q 0.019 -102.576 297.336 C_I 5.500 3.030 0.019 5.500 C_S 3.030 67.999 -102.576 3.030 67.999 C_Q 0.019 -102.576 297.336 0.019 -102.576 Covariances C_Q ________ C_Q 297.336 Correlations I S Q C_I C_S ________ ________ ________ ________ ________ I 1.000 S 0.157 1.000 Q 0.000 -0.721 1.000 C_I 1.000 0.157 0.000 1.000 C_S 0.157 1.000 -0.721 0.157 1.000 C_Q 0.000 -0.721 1.000 0.000 -0.721 Correlations C_Q ________ C_Q 1.000 PLOT INFORMATION The following plots are available: Histograms (sample values, estimated factor scores, estimated values) Scatterplots (sample values, estimated factor scores, estimated values) Sample means Estimated means Sample and estimated means Adjusted estimated means Observed individual values Estimated individual values Estimated means and observed individual values Estimated means and estimated individual values Adjusted estimated means and observed individual values Adjusted estimated means and estimated individual values Mixture distributions Estimated probabilities for a categorical latent variable as a function of its covariates Beginning Time: 11:28:57 Ending Time: 11:28:58 Elapsed Time: 00:00:01 MUTHEN & MUTHEN 3463 Stoner Ave. Los Angeles, CA 90066 Tel: (310) 391-9971 Fax: (310) 391-8971 Web: www.StatModel.com Support: Support@StatModel.com Copyright (c) 1998-2010 Muthen & Muthen