LEM: log-linear and event history analysis with missing data. Developed by Jeroen K. Vermunt (c), Tilburg University, The Netherlands. Version 1.2 (July 10, 1998). *** INPUT *** * Data generated from HCG/LMA (use formula for margin and multiply by 10000000 * ssq=.2; * uA= -.90 nuA = 1/sqrt(2) * uB= -.50 nuB = 1.500 * uC= -.20 nuC = .5000 * uD= .30 nuD = .8000 * uE= -.40 nuE = .9000 * uF= -.50 nuF = .2000 * uG= -.70 nuG = .4000 * * * Note LEM=gen as follows A=A, B=B C=C, C=D, D=E, F=G man 6 lat 1 dim 9 2 2 2 2 2 2 lab X A B C D E F mod X {wei(X)} A|X {A spe(A,1a,X,c,-1)} B|X {B spe(B,1a,X,c,-1)} C|X {C spe(C,1a,X,c,-1)} D|X {D spe(D,1a,X,c,-1)} E|X {E spe(E,1a,X,c,-1)} F|X {F spe(F,1a,X,c,-1)} des[-4.512745863399 -3.205429002856 -2.076847978677 -1.023255663789 0.000000000000 1.023255663789 2.076847978677 3.205429002856 4.512745863399 -4.512745863399 -3.205429002856 -2.076847978677 -1.023255663789 0.000000000000 1.023255663789 2.076847978677 3.205429002856 4.512745863399 -4.512745863399 -3.205429002856 -2.076847978677 -1.023255663789 0.000000000000 1.023255663789 2.076847978677 3.205429002856 4.512745863399 -4.512745863399 -3.205429002856 -2.076847978677 -1.023255663789 0.000000000000 1.023255663789 2.076847978677 3.205429002856 4.512745863399] -4.512745863399 -3.205429002856 -2.076847978677 -1.023255663789 0.000000000000 1.023255663789 2.076847978677 3.205429002856 4.512745863399 -4.512745863399 -3.205429002856 -2.076847978677 -1.023255663789 0.000000000000 1.023255663789 2.076847978677 3.205429002856 4.512745863399] sta wei(X) [0.000022345844 0.002789141321 0.049916406765 0.244097502895 0.406349206349 0.244097502895 0.049916406765 0.002789141321 0.000022345844] nco dat [ 14758.89 1816.15 1663.784 273.6234 7617.948 1213.113 1533.831 326.4057 4233.72 612.072 685.8199 132.5023 3016.199 564.265 872.5544 218.1248 5753.313 1147.944 1923.969 512.9549 7806.874 2015.461 4661.122 1607.752 3019.688 707.7887 1450.729 454.3359 5654.392 1714.731 4849.363 1964.699 779.1969 120.4235 146.6701 30.29198 634.3773 126.8658 213.2379 56.9822 297.1807 53.95692 80.37373 19.50004 333.9138 78.44583 161.2482 50.61497 713.7576 178.8369 398.4176 133.3773 1527.211 495.0661 1521.726 659.0059 497.991 146.5696 399.3021 157.0113 1470.241 559.8119 2104.059 1070.211 ] *** STATISTICS *** Number of iterations = 300 Converge criterion = 0.0000009956 Seed random values = 2182 X-squared = 11.4076 (1.0000) L-squared = 11.4192 (1.0000) Cressie-Read = 11.4113 (1.0000) Dissimilarity index = 0.0041 Degrees of freedom = 51 Log-likelihood = -339488.88582 Number of parameters = 12 (+1) Sample size = 100000.0 BIC(L-squared) = -575.7400 AIC(L-squared) = -90.5808 BIC(log-likelihood) = 679115.9268 AIC(log-likelihood) = 679001.7716 Eigenvalues information matrix 86590.3910 76531.2222 70820.6983 67983.4725 59562.1827 34121.1519 27384.6028 24102.1892 20407.4621 13290.9845 11494.9978 2485.1148 *** FREQUENCIES *** A B C D E F observed estimated std. res. 1 1 1 1 1 1 14758.890 14784.901 -0.214 1 1 1 1 1 2 1816.150 1809.228 0.163 1 1 1 1 2 1 1663.784 1652.349 0.281 1 1 1 1 2 2 273.623 276.085 -0.148 1 1 1 2 1 1 7617.948 7547.636 0.809 1 1 1 2 1 2 1213.113 1220.363 -0.208 1 1 1 2 2 1 1533.831 1553.479 -0.498 1 1 1 2 2 2 326.406 329.301 -0.160 1 1 2 1 1 1 4233.720 4203.504 0.466 1 1 2 1 1 2 612.072 613.951 -0.076 1 1 2 1 2 1 685.820 692.872 -0.268 1 1 2 1 2 2 132.502 134.671 -0.187 1 1 2 2 1 1 3016.199 3038.019 -0.396 1 1 2 2 1 2 564.265 573.127 -0.370 1 1 2 2 2 1 872.554 876.949 -0.148 1 1 2 2 2 2 218.125 213.978 0.283 1 2 1 1 1 1 5753.313 5678.394 0.994 1 2 1 1 1 2 1147.944 1157.124 -0.270 1 2 1 1 2 1 1923.969 1950.291 -0.596 1 2 1 1 2 2 512.955 515.011 -0.091 1 2 1 2 1 1 7806.874 7902.767 -1.079 1 2 1 2 1 2 2015.461 2023.944 -0.189 1 2 1 2 2 1 4661.122 4653.870 0.106 1 2 1 2 2 2 1607.752 1590.527 0.432 1 2 2 1 1 1 3019.688 3050.497 -0.558 1 2 2 1 1 2 707.789 715.052 -0.272 1 2 2 1 2 1 1450.729 1454.217 -0.091 1 2 2 1 2 2 454.336 449.239 0.240 1 2 2 2 1 1 5654.392 5667.955 -0.180 1 2 2 2 1 2 1714.731 1693.992 0.504 1 2 2 2 2 1 4849.363 4810.056 0.567 1 2 2 2 2 2 1964.699 1952.022 0.287 2 1 1 1 1 1 779.197 782.484 -0.118 2 1 1 1 1 2 120.424 122.284 -0.168 2 1 1 1 2 1 146.670 149.531 -0.234 2 1 1 1 2 2 30.292 30.784 -0.089 2 1 1 2 1 1 634.377 645.604 -0.442 2 1 1 2 1 2 126.866 129.114 -0.198 2 1 1 2 2 1 213.238 212.462 0.053 2 1 1 2 2 2 56.982 55.002 0.267 2 1 2 1 1 1 297.181 301.874 -0.270 2 1 2 1 1 2 53.957 55.214 -0.169 2 1 2 1 2 1 80.374 81.367 -0.110 2 1 2 1 2 2 19.500 19.270 0.052 2 1 2 2 1 1 333.914 338.767 -0.264 2 1 2 2 1 2 78.446 77.940 0.057 2 1 2 2 2 1 161.248 154.480 0.545 2 1 2 2 2 2 50.615 46.711 0.571 2 2 1 1 1 1 713.758 724.322 -0.393 2 2 1 1 1 2 178.837 179.911 -0.080 2 2 1 1 2 1 398.418 396.494 0.097 2 2 1 1 2 2 133.377 130.882 0.218 2 2 1 2 1 1 1527.211 1519.903 0.187 2 2 1 2 1 2 495.066 485.041 0.455 2 2 1 2 2 1 1521.726 1504.424 0.446 2 2 1 2 2 2 659.006 656.587 0.094 2 2 2 1 1 1 497.991 499.689 -0.076 2 2 2 1 1 2 146.570 144.464 0.175 2 2 2 1 2 1 399.302 392.193 0.359 2 2 2 1 2 2 157.011 153.428 0.289 2 2 2 2 1 1 1470.241 1440.523 0.783 2 2 2 2 1 2 559.812 543.850 0.684 2 2 2 2 2 1 2104.059 2119.798 -0.342 2 2 2 2 2 2 1070.211 1120.231 -1.494 *** PSEUDO R-SQUARED MEASURES *** * P(A|X) * baseline fitted R-squared entropy 0.4264 0.3737 0.1236 qualitative variance 0.1290 0.1141 0.1155 classification error 0.1522 0.1498 0.0157 -2/N*log-likelihood 0.8529 0.7475 0.1236/0.0954 likelihood^(-2/N) 2.3464 2.1116 0.1000/0.1743 * P(B|X) * baseline fitted R-squared entropy 0.6825 0.4299 0.3701 qualitative variance 0.2447 0.1399 0.4281 classification error 0.4272 0.2030 0.5248 -2/N*log-likelihood 1.3650 0.8598 0.3701/0.3356 likelihood^(-2/N) 3.9159 2.3627 0.3966/0.5326 * P(C|X) * baseline fitted R-squared entropy 0.6622 0.6119 0.0760 qualitative variance 0.2347 0.2119 0.0972 classification error 0.3763 0.3334 0.1140 -2/N*log-likelihood 1.3245 1.2238 0.0760/0.0914 likelihood^(-2/N) 3.7602 3.4001 0.0957/0.1304 * P(D|X) * baseline fitted R-squared entropy 0.6841 0.5716 0.1645 qualitative variance 0.2455 0.1948 0.2066 classification error 0.4330 0.2965 0.3153 -2/N*log-likelihood 1.3683 1.1433 0.1645/0.1837 likelihood^(-2/N) 3.9286 3.1370 0.2015/0.2703 * P(E|X) * baseline fitted R-squared entropy 0.6137 0.4953 0.1928 qualitative variance 0.2113 0.1636 0.2258 classification error 0.3033 0.2406 0.2067 -2/N*log-likelihood 1.2273 0.9907 0.1928/0.1914 likelihood^(-2/N) 3.4121 2.6931 0.2107/0.2981 * P(F|X) * baseline fitted R-squared entropy 0.4894 0.4666 0.0466 qualitative variance 0.1553 0.1480 0.0468 classification error 0.1922 0.1918 0.0020 -2/N*log-likelihood 0.9788 0.9331 0.0466/0.0436 likelihood^(-2/N) 2.6612 2.5425 0.0446/0.0714 *** LOG-LINEAR PARAMETERS *** * TABLE XA [or P(A|X)] * effect beta std err z-value exp(beta) Wald df prob A 1 1.0125 0.0066 154.197 2.7524 2 -1.0125 0.3633 23776.85 1 0.000 spe(A,1a) [X 1] 1 0.4965 0.0078 63.494 1.6429 4031.43 1 0.000 * TABLE XB [or P(B|X)] * effect beta std err z-value exp(beta) Wald df prob B 1 -0.2554 0.0061 -41.706 0.7746 2 0.2554 1.2910 1739.41 1 0.000 spe(B,1a) [X 1] 1 1.1136 0.0197 56.670 3.0452 3211.45 1 0.000 * TABLE XC [or P(C|X)] * effect beta std err z-value exp(beta) Wald df prob C 1 0.2807 0.0037 75.953 1.3241 2 -0.2807 0.7552 5768.82 1 0.000 spe(C,1a) [X 1] 1 0.3536 0.0054 65.922 1.4242 4345.70 1 0.000 * TABLE XD [or P(D|X)] * effect beta std err z-value exp(beta) Wald df prob D 1 -0.1701 0.0041 -41.619 0.8436 2 0.1701 1.1854 1732.17 1 0.000 spe(D,1a) [X 1] 1 0.5702 0.0072 78.876 1.7687 6221.35 1 0.000 * TABLE XE [or P(E|X)] * effect beta std err z-value exp(beta) Wald df prob E 1 0.5454 0.0052 104.464 1.7253 2 -0.5454 0.5796 10912.76 1 0.000 spe(E,1a) [X 1] 1 0.6427 0.0083 77.286 1.9017 5973.15 1 0.000 * TABLE XF [or P(F|X)] * effect beta std err z-value exp(beta) Wald df prob F 1 0.7644 0.0046 166.441 2.1477 2 -0.7644 0.4656 27702.68 1 0.000 spe(F,1a) [X 1] 1 0.2810 0.0059 47.936 1.3245 2297.89 1 0.000 *** LATENT CLASS OUTPUT *** X 1 X 2 X 3 X 4 X 5 X 6 X 7 X 8 0.0000 0.0028 0.0499 0.2441 0.4063 0.2441 0.0499 0.0028 A 1 0.0790 0.2390 0.4907 0.7328 0.8834 0.9544 0.9835 0.9946 A 2 0.9210 0.7610 0.5093 0.2672 0.1166 0.0456 0.0165 0.0054 B 1 0.0000 0.0005 0.0058 0.0579 0.3750 0.8542 0.9839 0.9987 B 2 1.0000 0.9995 0.9942 0.9421 0.6250 0.1458 0.0161 0.0013 C 1 0.0672 0.1538 0.2876 0.4595 0.6368 0.7833 0.8839 0.9442 C 2 0.9328 0.8462 0.7124 0.5405 0.3632 0.2167 0.1161 0.0558 D 1 0.0041 0.0181 0.0625 0.1813 0.4158 0.6957 0.8837 0.9650 D 2 0.9959 0.9819 0.9375 0.8187 0.5842 0.3043 0.1163 0.0350 E 1 0.0089 0.0461 0.1709 0.4441 0.7485 0.9173 0.9773 0.9946 E 2 0.9911 0.9539 0.8291 0.5559 0.2515 0.0827 0.0227 0.0054 F 1 0.2674 0.4322 0.5894 0.7218 0.8218 0.8913 0.9368 0.9655 F 2 0.7326 0.5678 0.4106 0.2782 0.1782 0.1087 0.0632 0.0345 X 9 0.0000 A 1 0.9985 A 2 0.0015 B 1 0.9999 B 2 0.0001 C 1 0.9771 C 2 0.0229 D 1 0.9919 D 2 0.0081 E 1 0.9990 E 2 0.0010 F 1 0.9831 F 2 0.0169 E = 0.4131, lambda = 0.3041