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 * LMA2 * man 5 dim 2 2 2 2 2 lab A B C D E mode {A B C D E ass2(A,B,-,7a) ass2(A,C,-,7a) ass2(A,D,-,7a) ass2(A,E,-,7a) ass2(B,C,-,7a) ass2(B,D,-,7a) ass2(B,E,-,7a) ass2(C,D,-,7a) ass2(C,E,-,7a) ass2(D,E,-,7a)} dlk ste 2 ass_equ [ 1 2 6 1 3 6 1 4 6 1 5 6 2 3 6 2 4 6 2 5 6 3 4 6 3 5 6 4 5 6 ] ass_res [ 0 2 3 0 2 3 0 2 3 0 2 3 2 2 3 2 2 3 2 2 3 2 2 3 2 2 3 2 2 3] ass_phi [ 1 1 1 1 1 1 1 1 1 1 ] ite 150000 nco data lsat7_dat.txt *** STATISTICS *** Number of iterations = 344 Converge criterion = 0.0000009882 X-squared = 33.2143 (0.0439) L-squared = 31.9671 (0.0590) Cressie-Read = 32.4750 (0.0524) Dissimilarity index = 0.0463 Degrees of freedom = 21 Log-likelihood = -2658.93839 Number of parameters = 10 (+1) Sample size = 1000.0 BIC(L-squared) = -113.0958 AIC(L-squared) = -10.0329 BIC(log-likelihood) = 5386.9543 AIC(log-likelihood) = 5337.8768 WARNING: no information is provided on identification of parameters *** FREQUENCIES *** A B C D E observed estimated std. res. 1 1 1 1 1 12.000 10.698 0.398 1 1 1 1 2 19.000 18.901 0.023 1 1 1 2 1 1.000 4.387 -1.617 1 1 1 2 2 7.000 10.301 -1.028 1 1 2 1 1 3.000 4.859 -0.843 1 1 2 1 2 19.000 15.596 0.862 1 1 2 2 1 3.000 3.816 -0.418 1 1 2 2 2 17.000 16.278 0.179 1 2 1 1 1 10.000 3.875 3.112 1 2 1 1 2 5.000 10.115 -1.608 1 2 1 2 1 3.000 2.430 0.366 1 2 1 2 2 7.000 8.431 -0.493 1 2 2 1 1 7.000 4.293 1.306 1 2 2 1 2 23.000 20.362 0.585 1 2 2 2 1 8.000 5.156 1.252 1 2 2 2 2 28.000 32.503 -0.790 2 1 1 1 1 7.000 12.902 -1.643 2 1 1 1 2 39.000 32.360 1.167 2 1 1 2 1 11.000 7.746 1.169 2 1 1 2 2 34.000 25.823 1.609 2 1 2 1 1 14.000 13.046 0.264 2 1 2 1 2 51.000 59.444 -1.095 2 1 2 2 1 15.000 15.000 -0.000 2 1 2 2 2 90.000 90.844 -0.089 2 2 1 1 1 6.000 7.886 -0.672 2 2 1 1 2 25.000 29.228 -0.782 2 2 1 2 1 7.000 7.242 -0.090 2 2 1 2 2 35.000 35.675 -0.113 2 2 2 1 1 18.000 19.453 -0.329 2 2 2 1 2 136.000 130.982 0.438 2 2 2 2 1 32.000 34.211 -0.378 2 2 2 2 2 308.000 306.158 0.105 *** LOG-LINEAR PARAMETERS *** * TABLE ABCDE [or P(ABCDE)] * effect beta exp(beta) main 2.7236 15.2351 A 1 -0.6075 0.5447 2 0.6075 1.8359 B 1 -0.0498 0.9514 2 0.0498 1.0511 C 1 -0.3401 0.7117 2 0.3401 1.4051 D 1 0.0106 1.0107 2 -0.0106 0.9894 E 1 -0.6902 0.5015 2 0.6902 1.9941 type 2 association (row=A column=B slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7880 0.7880 adj column -0.7880 0.7880 slab 0.2349 adj slab 0.2349 type 2 association (row=A column=C slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -1.2048 1.2048 adj column -1.2048 1.2048 slab 0.2349 adj slab 0.2349 type 2 association (row=A column=D slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.5741 0.5741 adj column -0.5741 0.5741 slab 0.2349 adj slab 0.2349 type 2 association (row=A column=E slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.5275 0.5275 adj column -0.5275 0.5275 slab 0.2349 adj slab 0.2349 type 2 association (row=B column=C slab=) association 1.0000 row -0.7880 0.7880 adj row -0.7880 0.7880 column -1.2048 1.2048 adj column -1.2048 1.2048 slab 0.2349 adj slab 0.2349 type 2 association (row=B column=D slab=) association 1.0000 row -0.7880 0.7880 adj row -0.7880 0.7880 column -0.5741 0.5741 adj column -0.5741 0.5741 slab 0.2349 adj slab 0.2349 type 2 association (row=B column=E slab=) association 1.0000 row -0.7880 0.7880 adj row -0.7880 0.7880 column -0.5275 0.5275 adj column -0.5275 0.5275 slab 0.2349 adj slab 0.2349 type 2 association (row=C column=D slab=) association 1.0000 row -1.2048 1.2048 adj row -1.2048 1.2048 column -0.5741 0.5741 adj column -0.5741 0.5741 slab 0.2349 adj slab 0.2349 type 2 association (row=C column=E slab=) association 1.0000 row -1.2048 1.2048 adj row -1.2048 1.2048 column -0.5275 0.5275 adj column -0.5275 0.5275 slab 0.2349 adj slab 0.2349 type 2 association (row=D column=E slab=) association 1.0000 row -0.5741 0.5741 adj row -0.5741 0.5741 column -0.5275 0.5275 adj column -0.5275 0.5275 slab 0.2349 adj slab 0.2349