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 *** * Generated probabilities from 2PL with theta normal(0,1) * a2= 1.7 b2= -1.05; * a3= .7 b3= -.35; * a4= 1.2 b4= .35; * a5= 1.7 b5= 1.05; * a6= .7 b6= 1.75; * a7= .2 b7= .50; * a8= .8 b8= -.50; * a9= .4 b9= -.70; lat 1 man 8 dim 9 2 2 2 2 2 2 2 2 lab X A B C D E F G H 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)} G|X {G spe(G,1a,X,c,-1)} H|X {H spe(H,1a,X,c,-1)} sta wei(X) [0.000022345844 0.002789141321 0.049916406765 0.244097502895 0.406349206349 0.244097502895 0.049916406765 0.002789141321 0.000022345844] 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 -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 ] nco dat gen8normal.dat *** STATISTICS *** Number of iterations = 126 Converge criterion = 0.0000009574 Seed random values = 4084 X-squared = 2.9667 (1.0000) L-squared = 2.9669 (1.0000) Cressie-Read = 2.9668 (1.0000) Dissimilarity index = 0.0007 Degrees of freedom = 239 Log-likelihood = -4872821.55276 Number of parameters = 16 (+1) Sample size = 999999.9 BIC(L-squared) = -3298.9401 AIC(L-squared) = -475.0331 BIC(log-likelihood) = 9745864.1537 AIC(log-likelihood) = 9745675.1055 Eigenvalues information matrix 9.36E+0005 8.91E+0005 8.82E+0005 8.41E+0005 7.50E+0005 6.61E+0005 6.25E+0005 5.32E+0005 4.42E+0005 3.64E+0005 3.19E+0005 2.87E+0005 1.90E+0005 1.88E+0005 82230.0791 60102.7781 *** FREQUENCIES *** A B C D E F G H observed estimated std. res. 1 1 1 1 1 1 1 1 11758.331 11754.017 0.040 1 1 1 1 1 1 1 2 3216.123 3218.189 -0.036 1 1 1 1 1 1 2 1 2335.600 2338.959 -0.069 1 1 1 1 1 1 2 2 741.370 742.040 -0.025 1 1 1 1 1 2 1 1 14246.749 14248.543 -0.015 1 1 1 1 1 2 1 2 4050.879 4054.886 -0.063 1 1 1 1 1 2 2 1 3051.672 3055.614 -0.071 1 1 1 1 1 2 2 2 1003.025 1003.256 -0.007 1 1 1 1 2 1 1 1 25060.950 25085.373 -0.154 1 1 1 1 2 1 1 2 7814.958 7820.915 -0.067 1 1 1 1 2 1 2 1 6426.938 6425.167 0.022 1 1 1 1 2 1 2 2 2297.196 2292.992 0.088 1 1 1 1 2 2 1 1 32451.536 32483.601 -0.178 1 1 1 1 2 2 1 2 10482.992 10485.304 -0.023 1 1 1 1 2 2 2 1 8916.612 8906.719 0.105 1 1 1 1 2 2 2 2 3292.120 3284.369 0.135 1 1 1 2 1 1 1 1 4427.859 4422.169 0.086 1 1 1 2 1 1 1 2 1634.819 1630.542 0.106 1 1 1 2 1 1 2 1 1581.662 1577.761 0.098 1 1 1 2 1 1 2 2 661.751 661.164 0.023 1 1 1 2 1 2 1 1 6244.426 6231.407 0.165 1 1 1 2 1 2 1 2 2380.242 2373.499 0.138 1 1 1 2 1 2 2 1 2375.414 2371.000 0.091 1 1 1 2 1 2 2 2 1024.535 1024.783 -0.008 1 1 1 2 2 1 1 1 15814.079 15768.504 0.363 1 1 1 2 2 1 1 2 6515.951 6505.391 0.131 1 1 1 2 2 1 2 1 7017.718 7022.833 -0.061 1 1 1 2 2 1 2 2 3263.111 3271.656 -0.149 1 1 1 2 2 2 1 1 23568.395 23510.470 0.378 1 1 1 2 2 2 1 2 10012.162 10006.695 0.055 1 1 1 2 2 2 2 1 11112.642 11132.605 -0.189 1 1 1 2 2 2 2 2 5323.884 5339.938 -0.220 1 1 2 1 1 1 1 1 3492.943 3497.031 -0.069 1 1 2 1 1 1 1 2 1187.848 1187.422 0.012 1 1 2 1 1 1 2 1 1061.432 1059.609 0.056 1 1 2 1 1 1 2 2 411.026 410.152 0.043 1 1 2 1 1 2 1 1 4725.723 4727.883 -0.031 1 1 2 1 1 2 1 2 1661.593 1659.571 0.050 1 1 2 1 1 2 2 1 1533.273 1529.997 0.084 1 1 2 1 1 2 2 2 612.569 611.517 0.043 1 1 2 1 2 1 1 1 10823.170 10804.768 0.177 1 1 2 1 2 1 1 2 4125.561 4115.487 0.157 1 1 2 1 2 1 2 1 4117.193 4111.180 0.094 1 1 2 1 2 1 2 2 1775.778 1776.927 -0.027 1 1 2 1 2 2 1 1 15510.726 15475.625 0.282 1 1 2 1 2 2 1 2 6101.143 6087.538 0.174 1 1 2 1 2 2 2 1 6278.520 6275.290 0.041 1 1 2 1 2 2 2 2 2790.969 2795.953 -0.094 1 1 2 2 1 1 1 1 3117.821 3114.876 0.053 1 1 2 2 1 1 1 2 1385.954 1387.721 -0.047 1 1 2 2 1 1 2 1 1608.943 1613.490 -0.113 1 1 2 2 1 1 2 2 806.117 808.223 -0.074 1 1 2 2 1 2 1 1 4827.066 4827.789 -0.010 1 1 2 2 1 2 1 2 2211.156 2216.000 -0.103 1 1 2 2 1 2 2 1 2644.704 2652.488 -0.151 1 1 2 2 1 2 2 2 1365.279 1367.811 -0.068 1 1 2 2 2 1 1 1 15374.051 15411.543 -0.302 1 1 2 2 2 1 1 2 7588.607 7609.247 -0.237 1 1 2 2 2 1 2 1 9780.936 9793.423 -0.126 1 1 2 2 2 1 2 2 5444.303 5439.074 0.071 1 1 2 2 2 2 1 1 25083.320 25153.589 -0.443 1 1 2 2 2 2 1 2 12756.505 12784.196 -0.245 1 1 2 2 2 2 2 1 16943.917 16946.629 -0.021 1 1 2 2 2 2 2 2 9723.575 9704.758 0.191 1 2 1 1 1 1 1 1 3068.874 3072.791 -0.071 1 2 1 1 1 1 1 2 956.992 957.984 -0.032 1 2 1 1 1 1 2 1 787.020 786.998 0.001 1 2 1 1 1 1 2 2 281.306 280.854 0.027 1 2 1 1 1 2 1 1 3973.899 3978.970 -0.080 1 2 1 1 1 2 1 2 1283.710 1284.328 -0.017 1 2 1 1 1 2 2 1 1091.897 1090.941 0.029 1 2 1 1 1 2 2 2 403.141 402.276 0.043 1 2 1 1 2 1 1 1 8190.874 8190.991 -0.001 1 2 1 1 2 1 1 2 2879.961 2875.456 0.084 1 2 1 1 2 1 2 1 2657.550 2651.196 0.123 1 2 1 1 2 1 2 2 1061.737 1059.740 0.061 1 2 1 1 2 2 1 1 11269.992 11261.056 0.084 1 2 1 1 2 2 1 2 4094.396 4085.312 0.142 1 2 1 1 2 2 2 1 3899.704 3890.477 0.148 1 2 1 1 2 2 2 2 1606.814 1605.135 0.042 1 2 1 2 1 1 1 1 1936.536 1931.324 0.119 1 2 1 2 1 1 1 2 797.920 796.760 0.041 1 2 1 2 1 1 2 1 859.365 860.114 -0.026 1 2 1 2 1 1 2 2 399.589 400.683 -0.055 1 2 1 2 1 2 1 1 2886.101 2879.522 0.123 1 2 1 2 1 2 1 2 1226.054 1225.574 0.014 1 2 1 2 1 2 2 1 1360.814 1363.438 -0.071 1 2 1 2 1 2 2 2 651.944 653.981 -0.080 1 2 1 2 2 1 1 1 8366.527 8367.329 -0.009 1 2 1 2 2 1 1 2 3832.493 3841.006 -0.137 1 2 1 2 2 1 2 1 4583.942 4597.955 -0.207 1 2 1 2 2 1 2 2 2366.374 2371.230 -0.100 1 2 1 2 2 2 1 1 13149.568 13165.853 -0.142 1 2 1 2 2 2 1 2 6206.377 6223.985 -0.223 1 2 1 2 2 2 2 1 7648.225 7669.256 -0.240 1 2 1 2 2 2 2 2 4068.527 4072.816 -0.067 1 2 2 1 1 1 1 1 1325.367 1323.408 0.054 1 2 2 1 1 1 1 2 505.202 504.067 0.051 1 2 2 1 1 1 2 1 504.177 503.527 0.029 1 2 2 1 1 1 2 2 217.455 217.629 -0.012 1 2 2 1 1 2 1 1 1899.388 1895.487 0.090 1 2 2 1 1 2 1 2 747.124 745.596 0.056 1 2 2 1 1 2 2 1 768.845 768.573 0.010 1 2 2 1 1 2 2 2 341.772 342.429 -0.036 1 2 2 1 2 1 1 1 5002.344 4992.922 0.133 1 2 2 1 2 1 1 2 2125.061 2125.085 -0.001 1 2 2 1 2 1 2 1 2358.636 2364.150 -0.113 1 2 2 1 2 1 2 2 1129.984 1133.985 -0.119 1 2 2 1 2 2 1 1 7570.455 7562.250 0.094 1 2 2 1 2 2 1 2 3314.936 3318.839 -0.068 1 2 2 1 2 2 2 1 3791.194 3803.058 -0.192 1 2 2 1 2 2 2 2 1871.328 1877.812 -0.150 1 2 2 2 1 1 1 1 1882.651 1887.469 -0.111 1 2 2 2 1 1 1 2 929.274 931.892 -0.086 1 2 2 2 1 1 2 1 1197.738 1199.357 -0.047 1 2 2 2 1 1 2 2 666.690 666.084 0.023 1 2 2 2 1 2 1 1 3071.614 3080.554 -0.161 1 2 2 2 1 2 1 2 1562.116 1565.642 -0.089 1 2 2 2 1 2 2 1 2074.892 2075.355 -0.010 1 2 2 2 1 2 2 2 1190.714 1188.456 0.065 1 2 2 2 2 1 1 1 11149.101 11168.641 -0.185 1 2 2 2 2 1 1 2 6112.483 6109.987 0.032 1 2 2 2 2 1 2 1 8761.276 8740.603 0.221 1 2 2 2 2 1 2 2 5434.183 5418.127 0.218 1 2 2 2 2 2 1 1 19168.743 19182.544 -0.100 1 2 2 2 2 2 1 2 10833.428 10817.417 0.154 1 2 2 2 2 2 2 1 16016.647 15970.872 0.362 1 2 2 2 2 2 2 2 10255.634 10227.991 0.273 2 1 1 1 1 1 1 1 542.220 541.527 0.030 2 1 1 1 1 1 1 2 200.194 199.708 0.034 2 1 1 1 1 1 2 1 193.685 193.277 0.029 2 1 1 1 1 1 2 2 81.036 81.007 0.003 2 1 1 1 1 2 1 1 764.670 763.151 0.055 2 1 1 1 1 2 1 2 291.476 290.730 0.044 2 1 1 1 1 2 2 1 290.885 290.475 0.024 2 1 1 1 1 2 2 2 125.461 125.569 -0.010 2 1 1 1 2 1 1 1 1936.536 1931.573 0.113 2 1 1 1 2 1 1 2 797.920 797.020 0.032 2 1 1 1 2 1 2 1 859.365 860.559 -0.041 2 1 1 1 2 1 2 2 399.589 400.965 -0.069 2 1 1 1 2 2 1 1 2886.101 2880.180 0.110 2 1 1 1 2 2 1 2 1226.054 1226.092 -0.001 2 1 1 1 2 2 2 1 1360.814 1364.270 -0.094 2 1 1 1 2 2 2 2 651.944 654.499 -0.100 2 1 1 2 1 1 1 1 675.760 677.117 -0.052 2 1 1 2 1 1 1 2 323.746 324.817 -0.059 2 1 1 2 1 1 2 1 404.963 406.111 -0.057 2 1 1 2 1 1 2 2 218.692 218.905 -0.014 2 1 1 2 1 2 1 1 1086.195 1089.290 -0.094 2 1 1 2 1 2 1 2 536.144 537.905 -0.076 2 1 1 2 1 2 2 1 691.035 692.414 -0.052 2 1 1 2 1 2 2 2 384.647 384.615 0.002 2 1 1 2 2 1 1 1 3797.996 3809.444 -0.185 2 1 1 2 2 1 1 2 2020.371 2023.250 -0.064 2 1 1 2 2 1 2 1 2808.461 2806.671 0.034 2 1 1 2 2 1 2 2 1688.142 1685.132 0.073 2 1 1 2 2 2 1 1 6432.472 6447.601 -0.188 2 1 1 2 2 2 1 2 3526.596 3527.909 -0.022 2 1 1 2 2 2 2 1 5054.817 5047.787 0.099 2 1 1 2 2 2 2 2 3135.251 3129.639 0.100 2 1 2 1 1 1 1 1 381.797 381.641 0.008 2 1 2 1 1 1 1 2 169.719 170.054 -0.026 2 1 2 1 1 1 2 1 197.025 197.752 -0.052 2 1 2 1 1 1 2 2 98.714 99.073 -0.036 2 1 2 1 1 2 1 1 591.105 591.560 -0.019 2 1 2 1 1 2 1 2 270.770 271.575 -0.049 2 1 2 1 1 2 2 1 323.861 325.120 -0.070 2 1 2 1 1 2 2 2 167.187 167.682 -0.038 2 1 2 1 2 1 1 1 1882.651 1888.793 -0.141 2 1 2 1 2 1 1 2 929.274 932.715 -0.113 2 1 2 1 2 1 2 1 1197.738 1200.637 -0.084 2 1 2 1 2 1 2 2 666.690 666.922 -0.009 2 1 2 1 2 2 1 1 3071.614 3082.995 -0.205 2 1 2 1 2 2 1 2 1562.116 1567.168 -0.128 2 1 2 1 2 2 2 1 2074.892 2077.766 -0.063 2 1 2 1 2 2 2 2 1190.714 1190.068 0.019 2 1 2 2 1 1 1 1 1030.361 1031.000 -0.020 2 1 2 2 1 1 1 2 591.291 590.471 0.034 2 1 2 2 1 1 2 1 887.968 885.893 0.070 2 1 2 2 1 1 2 2 577.808 576.795 0.042 2 1 2 2 1 2 1 1 1812.251 1811.400 0.020 2 1 2 2 1 2 1 2 1072.535 1070.373 0.066 2 1 2 2 1 2 2 1 1662.374 1658.700 0.090 2 1 2 2 1 2 2 2 1117.610 1116.391 0.036 2 1 2 2 2 1 1 1 7953.632 7935.633 0.202 2 1 2 2 2 1 1 2 5092.797 5082.704 0.142 2 1 2 2 2 1 2 1 8561.914 8555.121 0.073 2 1 2 2 2 1 2 2 6263.747 6266.856 -0.039 2 1 2 2 2 2 1 1 14771.640 14737.544 0.281 2 1 2 2 2 2 1 2 9769.457 9755.887 0.137 2 1 2 2 2 2 2 1 16985.611 16984.216 0.011 2 1 2 2 2 2 2 2 12871.159 12882.185 -0.097 2 2 1 1 1 1 1 1 237.141 236.579 0.037 2 2 1 1 1 1 1 2 97.710 97.616 0.010 2 2 1 1 1 1 2 1 105.235 105.396 -0.016 2 2 1 1 1 1 2 2 48.932 49.107 -0.025 2 2 1 1 1 2 1 1 353.422 352.760 0.035 2 2 1 1 1 2 1 2 150.138 150.166 -0.002 2 2 1 1 1 2 2 1 166.640 167.086 -0.034 2 2 1 1 1 2 2 2 79.835 80.156 -0.036 2 2 1 1 2 1 1 1 1024.535 1025.267 -0.023 2 2 1 1 2 1 1 2 469.313 470.724 -0.065 2 2 1 1 2 1 2 1 561.333 563.579 -0.095 2 2 1 1 2 1 2 2 289.778 290.692 -0.054 2 2 1 1 2 2 1 1 1610.249 1613.374 -0.078 2 2 1 1 2 2 1 2 760.011 762.824 -0.102 2 2 1 1 2 2 2 1 936.574 940.109 -0.115 2 2 1 1 2 2 2 2 498.217 499.333 -0.050 2 2 1 2 1 1 1 1 465.089 466.534 -0.067 2 2 1 2 1 1 1 2 247.407 247.777 -0.023 2 2 1 2 1 1 2 1 343.914 343.710 0.011 2 2 1 2 1 1 2 2 206.724 206.359 0.025 2 2 1 2 1 2 1 1 787.697 789.614 -0.068 2 2 1 2 1 2 1 2 431.854 432.040 -0.009 2 2 1 2 1 2 2 1 618.995 618.154 0.034 2 2 1 2 1 2 2 2 383.932 383.247 0.035 2 2 1 2 2 1 1 1 3141.089 3140.572 0.009 2 2 1 2 2 1 1 2 1858.974 1855.962 0.070 2 2 1 2 2 1 2 1 2881.315 2876.353 0.093 2 2 1 2 2 1 2 2 1937.101 1936.119 0.022 2 2 1 2 2 2 1 1 5610.015 5604.128 0.079 2 2 1 2 2 2 1 2 3425.270 3419.036 0.107 2 2 1 2 2 2 2 1 5482.087 5475.389 0.091 2 2 1 2 2 2 2 2 3810.267 3811.299 -0.017 2 2 2 1 1 1 1 1 230.543 231.323 -0.051 2 2 2 1 1 1 1 2 113.796 114.228 -0.040 2 2 2 1 1 1 2 1 146.671 147.037 -0.030 2 2 2 1 1 1 2 2 81.640 81.673 -0.004 2 2 2 1 1 2 1 1 376.139 377.574 -0.074 2 2 2 1 1 2 1 2 191.291 191.926 -0.046 2 2 2 1 1 2 2 1 254.084 254.452 -0.023 2 2 2 1 1 2 2 2 145.811 145.737 0.006 2 2 2 1 2 1 1 1 1365.279 1369.178 -0.105 2 2 2 1 2 1 1 2 748.513 749.155 -0.023 2 2 2 1 2 1 2 1 1072.875 1071.883 0.030 2 2 2 1 2 1 2 2 665.451 664.558 0.035 2 2 2 1 2 2 1 1 2347.336 2351.806 -0.092 2 2 2 1 2 2 1 2 1326.623 1326.454 0.005 2 2 2 1 2 2 2 1 1961.341 1958.724 0.059 2 2 2 1 2 2 2 2 1255.868 1254.623 0.035 2 2 2 2 1 1 1 1 973.973 971.789 0.070 2 2 2 2 1 1 1 2 623.646 622.407 0.050 2 2 2 2 1 1 2 1 1048.461 1047.597 0.027 2 2 2 2 1 1 2 2 767.036 767.372 -0.012 2 2 2 2 1 2 1 1 1808.882 1804.721 0.098 2 2 2 2 1 2 1 2 1196.333 1194.649 0.049 2 2 2 2 1 2 2 1 2079.997 2079.734 0.006 2 2 2 2 1 2 2 2 1576.156 1577.393 -0.031 2 2 2 2 2 1 1 1 9126.595 9116.339 0.107 2 2 2 2 2 1 1 2 6562.526 6564.361 -0.023 2 2 2 2 2 1 2 1 12452.411 12462.407 -0.090 2 2 2 2 2 1 2 2 10345.766 10351.321 -0.055 2 2 2 2 2 2 1 1 17951.960 17945.030 0.052 2 2 2 2 2 2 1 2 13364.883 13375.088 -0.088 2 2 2 2 2 2 2 1 26303.930 26324.390 -0.126 2 2 2 2 2 2 2 2 22715.980 22719.748 -0.025 *** PSEUDO R-SQUARED MEASURES *** * P(A|X) * baseline fitted R-squared entropy 0.6352 0.4587 0.2779 qualitative variance 0.2216 0.1498 0.3241 classification error 0.3314 0.2054 0.3801 -2/N*log-likelihood 1.2703 0.9173 0.2779/0.2609 likelihood^(-2/N) 3.5620 2.5026 0.2974/0.4135 * P(B|X) * baseline fitted R-squared entropy 0.6809 0.6298 0.0751 qualitative variance 0.2439 0.2200 0.0980 classification error 0.4218 0.3505 0.1690 -2/N*log-likelihood 1.3618 1.2595 0.0751/0.0927 likelihood^(-2/N) 3.9030 3.5238 0.0972/0.1306 * P(C|X) * baseline fitted R-squared entropy 0.6840 0.5632 0.1766 qualitative variance 0.2454 0.1913 0.2207 classification error 0.4324 0.2896 0.3301 -2/N*log-likelihood 1.3679 1.1263 0.1766/0.1946 likelihood^(-2/N) 3.9273 3.0842 0.2147/0.2880 * P(D|X) * baseline fitted R-squared entropy 0.6352 0.4588 0.2777 qualitative variance 0.2216 0.1498 0.3239 classification error 0.3314 0.2055 0.3798 -2/N*log-likelihood 1.2703 0.9176 0.2777/0.2608 likelihood^(-2/N) 3.5620 2.5033 0.2972/0.4132 * P(E|X) * baseline fitted R-squared entropy 0.4532 0.4223 0.0683 qualitative variance 0.1400 0.1309 0.0650 classification error 0.1683 0.1677 0.0041 -2/N*log-likelihood 0.9065 0.8446 0.0683/0.0583 likelihood^(-2/N) 2.4756 2.3270 0.0600/0.1007 * P(F|X) * baseline fitted R-squared entropy 0.6634 0.6588 0.0070 qualitative variance 0.2353 0.2331 0.0092 classification error 0.3787 0.3785 0.0005 -2/N*log-likelihood 1.3268 1.3175 0.0070/0.0092 likelihood^(-2/N) 3.7690 3.7342 0.0092/0.0126 * P(G|X) * baseline fitted R-squared entropy 0.6697 0.6068 0.0938 qualitative variance 0.2383 0.2097 0.1200 classification error 0.3921 0.3253 0.1704 -2/N*log-likelihood 1.3393 1.2137 0.0938/0.1116 likelihood^(-2/N) 3.8164 3.3658 0.1181/0.1600 * P(H|X) * baseline fitted R-squared entropy 0.6393 0.6223 0.0266 qualitative variance 0.2236 0.2160 0.0336 classification error 0.3374 0.3334 0.0120 -2/N*log-likelihood 1.2786 1.2447 0.0266/0.0328 likelihood^(-2/N) 3.5916 3.4717 0.0334/0.0463 *** LOG-LINEAR PARAMETERS *** * TABLE XA [or P(A|X)] * effect beta std err z-value exp(beta) Wald df prob A 1 0.5249 0.0019 271.681 1.6902 2 -0.5249 0.5916 73810.59 1 0.000 spe(A,1a) [X 1] 1 0.8499 0.0036 237.253 2.3395 56288.98 1 0.000 * TABLE XB [or P(B|X)] * effect beta std err z-value exp(beta) Wald df prob B 1 0.1750 0.0011 154.559 1.1912 2 -0.1750 0.8395 23888.37 1 0.000 spe(B,1a) [X 1] 1 0.3498 0.0017 211.770 1.4188 44846.74 1 0.000 * TABLE XC [or P(C|X)] * effect beta std err z-value exp(beta) Wald df prob C 1 -0.1749 0.0013 -132.729 0.8395 2 0.1749 1.1912 17616.90 1 0.000 spe(C,1a) [X 1] 1 0.5995 0.0023 258.580 1.8211 66863.55 1 0.000 * TABLE XD [or P(D|X)] * effect beta std err z-value exp(beta) Wald df prob D 1 -0.5247 0.0019 -272.387 0.5917 2 0.5247 1.6899 74194.78 1 0.000 spe(D,1a) [X 1] 1 0.8494 0.0036 238.874 2.3382 57060.73 1 0.000 * TABLE XE [or P(E|X)] * effect beta std err z-value exp(beta) Wald df prob E 1 -0.8750 0.0016 -530.342 0.4169 2 0.8750 2.3988 281262.69 1 0.000 spe(E,1a) [X 1] 1 0.3499 0.0020 171.654 1.4189 29465.06 1 0.000 * TABLE XF [or P(F|X)] * effect beta std err z-value exp(beta) Wald df prob F 1 -0.2500 0.0010 -239.827 0.7788 2 0.2500 1.2840 57516.77 1 0.000 spe(F,1a) [X 1] 1 0.1000 0.0014 73.149 1.1051 5350.75 1 0.000 * TABLE XG [or P(G|X)] * effect beta std err z-value exp(beta) Wald df prob G 1 0.2500 0.0012 210.391 1.2840 2 -0.2500 0.7788 44264.33 1 0.000 spe(G,1a) [X 1] 1 0.3998 0.0018 226.049 1.4915 51097.93 1 0.000 * TABLE XH [or P(H|X)] * effect beta std err z-value exp(beta) Wald df prob H 1 0.3500 0.0011 315.619 1.4191 2 -0.3500 0.7047 99615.23 1 0.000 spe(H,1a) [X 1] 1 0.1999 0.0015 134.801 1.2213 18171.38 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 0.0013 0.0121 0.0772 0.3341 0.7407 0.9421 0.9898 0.9985 A 2 0.9987 0.9879 0.9228 0.6659 0.2593 0.0579 0.0102 0.0015 B 1 0.0569 0.1309 0.2492 0.4095 0.5866 0.7438 0.8585 0.9304 B 2 0.9431 0.8691 0.7508 0.5905 0.4134 0.2562 0.1415 0.0696 C 1 0.0031 0.0149 0.0552 0.1713 0.4134 0.7062 0.8947 0.9705 C 2 0.9969 0.9851 0.9448 0.8287 0.5866 0.2938 0.1053 0.0295 D 1 0.0002 0.0015 0.0102 0.0580 0.2593 0.6657 0.9226 0.9878 D 2 0.9998 0.9985 0.9898 0.9420 0.7407 0.3343 0.0774 0.0122 E 1 0.0073 0.0181 0.0390 0.0783 0.1481 0.2623 0.4264 0.6209 E 2 0.9927 0.9819 0.9610 0.9217 0.8519 0.7377 0.5736 0.3791 F 1 0.1975 0.2422 0.2859 0.3308 0.3775 0.4267 0.4788 0.5352 F 2 0.8025 0.7578 0.7141 0.6692 0.6225 0.5733 0.5212 0.4648 G 1 0.0428 0.1128 0.2386 0.4211 0.6224 0.7889 0.8966 0.9553 G 2 0.9572 0.8872 0.7614 0.5789 0.3776 0.2111 0.1034 0.0447 H 1 0.2489 0.3585 0.4674 0.5722 0.6682 0.7520 0.8221 0.8789 H 2 0.7511 0.6415 0.5326 0.4278 0.3318 0.2480 0.1779 0.1211 X 9 0.0000 A 1 0.9998 A 2 0.0002 B 1 0.9709 B 2 0.0291 C 1 0.9937 C 2 0.0063 D 1 0.9987 D 2 0.0013 E 1 0.8035 E 2 0.1965 F 1 0.5992 F 2 0.4008 G 1 0.9838 G 2 0.0162 H 1 0.9245 H 2 0.0755 E = 0.4121, lambda = 0.3058