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 *** * LSAT 7 data * Fitting rasch via MMLE (i.e., one dimensional model) * man 5 lat 1 dim 9 2 2 2 2 2 lab X A B C D E mod X {wei(X)} A|X {A} B|X {B} C|X {C} D|X {D} E|X {E} all {spe(XA,XB,XC,XD,XE,1b)} sta wei(X) nor(0,1) ite 150000 nco data lsat7_dat.txt *** STATISTICS *** Number of iterations = 50 Converge criterion = 0.0000008305 Seed random values = 2344 X-squared = 44.1590 (0.0104) L-squared = 43.7409 (0.0116) Cressie-Read = 43.7346 (0.0116) Dissimilarity index = 0.0641 Degrees of freedom = 25 Log-likelihood = -2664.82527 Number of parameters = 6 (+1) Sample size = 1000.0 BIC(L-squared) = -128.9530 AIC(L-squared) = -6.2591 BIC(log-likelihood) = 5371.0971 AIC(log-likelihood) = 5341.6505 Eigenvalues information matrix 775.5775 683.0505 555.7521 478.6680 360.0235 123.5994 *** FREQUENCIES *** A B C D E observed estimated std. res. 1 1 1 1 1 12.000 11.160 0.251 1 1 1 1 2 19.000 14.468 1.191 1 1 1 2 1 1.000 3.320 -1.273 1 1 1 2 2 7.000 7.382 -0.141 1 1 2 1 1 3.000 8.488 -1.884 1 1 2 1 2 19.000 18.873 0.029 1 1 2 2 1 3.000 4.331 -0.640 1 1 2 2 2 17.000 16.252 0.186 1 2 1 1 1 10.000 4.344 2.714 1 2 1 1 2 5.000 9.659 -1.499 1 2 1 2 1 3.000 2.216 0.526 1 2 1 2 2 7.000 8.317 -0.457 1 2 2 1 1 7.000 5.666 0.560 1 2 2 1 2 23.000 21.264 0.377 1 2 2 2 1 8.000 4.880 1.413 1 2 2 2 2 28.000 31.320 -0.593 2 1 1 1 1 7.000 12.767 -1.614 2 1 1 1 2 39.000 28.386 1.992 2 1 1 2 1 11.000 6.514 1.758 2 1 1 2 2 34.000 24.445 1.933 2 1 2 1 1 14.000 16.653 -0.650 2 1 2 1 2 51.000 62.493 -1.454 2 1 2 2 1 15.000 14.341 0.174 2 1 2 2 2 90.000 92.047 -0.213 2 2 1 1 1 6.000 8.523 -0.864 2 2 1 1 2 25.000 31.982 -1.235 2 2 1 2 1 7.000 7.339 -0.125 2 2 1 2 2 35.000 47.108 -1.764 2 2 2 1 1 18.000 18.763 -0.176 2 2 2 1 2 136.000 120.431 1.419 2 2 2 2 1 32.000 27.637 0.830 2 2 2 2 2 308.000 308.631 -0.036 *** PSEUDO R-SQUARED MEASURES *** * P(A|X) * baseline fitted R-squared entropy 0.4590 0.3992 0.1303 qualitative variance 0.1424 0.1239 0.1297 classification error 0.1720 0.1640 0.0467 -2/N*log-likelihood 0.9181 0.7920 0.1373/0.1120 likelihood^(-2/N) 2.5045 2.2078 0.1185/0.1972 * P(B|X) * baseline fitted R-squared entropy 0.6424 0.5558 0.1347 qualitative variance 0.2250 0.1880 0.1648 classification error 0.3420 0.2728 0.2022 -2/N*log-likelihood 1.2847 1.1143 0.1326/0.1456 likelihood^(-2/N) 3.6136 3.0475 0.1567/0.2166 * P(C|X) * baseline fitted R-squared entropy 0.5368 0.4657 0.1326 qualitative variance 0.1760 0.1504 0.1458 classification error 0.2280 0.2165 0.0504 -2/N*log-likelihood 1.0737 0.9027 0.1592/0.1460 likelihood^(-2/N) 2.9262 2.4663 0.1571/0.2387 * P(D|X) * baseline fitted R-squared entropy 0.6705 0.5800 0.1350 qualitative variance 0.2388 0.1984 0.1691 classification error 0.3940 0.2975 0.2449 -2/N*log-likelihood 1.3410 1.1738 0.1247/0.1433 likelihood^(-2/N) 3.8229 3.2342 0.1540/0.2085 * P(E|X) * baseline fitted R-squared entropy 0.4347 0.3784 0.1294 qualitative variance 0.1324 0.1159 0.1244 classification error 0.1570 0.1502 0.0436 -2/N*log-likelihood 0.8693 0.7754 0.1081/0.0859 likelihood^(-2/N) 2.3853 2.1714 0.0897/0.1544 *** LOG-LINEAR PARAMETERS *** * TABLE XA [or P(A|X)] * effect beta std err z-value exp(beta) Wald df prob A 1 -0.9333 0.0501 -18.619 0.3932 2 0.9333 2.5430 346.67 1 0.000 * TABLE XB [or P(B|X)] * effect beta std err z-value exp(beta) Wald df prob B 1 -0.3943 0.0404 -9.767 0.6741 2 0.3943 1.4834 95.40 1 0.000 * TABLE XC [or P(C|X)] * effect beta std err z-value exp(beta) Wald df prob C 1 -0.7292 0.0455 -16.023 0.4823 2 0.7292 2.0735 256.75 1 0.000 * TABLE XD [or P(D|X)] * effect beta std err z-value exp(beta) Wald df prob D 1 -0.2599 0.0391 -6.639 0.7711 2 0.2599 1.2968 44.08 1 0.000 * TABLE XE [or P(E|X)] * effect beta std err z-value exp(beta) Wald df prob E 1 -0.9959 0.0518 -19.231 0.3694 2 0.9959 2.7071 369.81 1 0.000 * ALL TABLES * effect beta std err z-value exp(beta) Wald df prob spe(XA,.,XE,1b) 1 -1.2957 0.0842 -15.397 0.2737 237.07 1 0.000 *** LATENT CLASS OUTPUT *** X 1 X 2 X 3 X 4 X 5 X 6 X 7 X 8 0.0001 0.0011 0.0205 0.2149 0.5269 0.2149 0.0205 0.0011 A 1 0.0009 0.0032 0.0115 0.0406 0.1339 0.3610 0.6736 0.8829 A 2 0.9991 0.9968 0.9885 0.9594 0.8661 0.6390 0.3264 0.1171 B 1 0.0025 0.0092 0.0329 0.1106 0.3125 0.6241 0.8585 0.9568 B 2 0.9975 0.9908 0.9671 0.8894 0.6875 0.3759 0.1415 0.0432 C 1 0.0013 0.0047 0.0171 0.0599 0.1887 0.4594 0.7564 0.9190 C 2 0.9987 0.9953 0.9829 0.9401 0.8113 0.5406 0.2436 0.0810 D 1 0.0033 0.0120 0.0426 0.1400 0.3729 0.6848 0.8881 0.9667 D 2 0.9967 0.9880 0.9574 0.8600 0.6271 0.3152 0.1119 0.0333 E 1 0.0008 0.0028 0.0101 0.0360 0.1201 0.3327 0.6456 0.8694 E 2 0.9992 0.9972 0.9899 0.9640 0.8799 0.6673 0.3544 0.1306 X 9 0.0001 A 1 0.9650 A 2 0.0350 B 1 0.9878 B 2 0.0122 C 1 0.9764 C 2 0.0236 D 1 0.9906 D 2 0.0094 E 1 0.9605 E 2 0.0395 E = 0.4044, lambda = 0.1453