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 Rasch with theta normal(0,1) * * b2= -1.05; * b3= -.35; * b4= .35; * b5= 1.05; * man 4 dim 2 2 2 2 lab A B C D mod { A B C D ass2(A,B,-,7a) ass2(A,C,-,7a) ass2(A,D,-,7a) ass2(B,C,-,7a) ass2(B,D,-,7a) ass2(C,D,-,7a) } ass_equ [ 1 2 5 1 3 5 1 4 5 2 3 5 2 4 5 3 4 5 ] ass_res [ 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 ] ass_phi [ 1 1 1 1 1 1 ] nco dat gen4rasch_normal.dat *** STATISTICS *** Number of iterations = 16 Converge criterion = 0.0000005239 X-squared = 1.9530 (0.9967) L-squared = 1.9530 (0.9967) Cressie-Read = 1.9530 (0.9967) Dissimilarity index = 0.0007 Degrees of freedom = 10 Log-likelihood = -2513557.07138 Number of parameters = 5 (+1) Sample size = 1000000.0 BIC(L-squared) = -136.2021 AIC(L-squared) = -18.0470 BIC(log-likelihood) = 5027183.2203 AIC(log-likelihood) = 5027124.1428 WARNING: no information is provided on identification of parameters *** FREQUENCIES *** A B C D observed estimated std. res. 1 1 1 1 106140.150 106055.067 0.261 1 1 1 2 129889.460 130067.663 -0.494 1 1 2 1 64501.198 64598.435 -0.383 1 1 2 2 139466.040 139240.216 0.605 1 2 1 1 32030.347 32072.039 -0.233 1 2 1 2 69256.785 69130.431 0.481 1 2 2 1 34391.902 34333.804 0.314 1 2 2 2 129889.460 130067.680 -0.494 2 1 1 1 15905.800 15928.658 -0.181 2 1 1 2 34391.902 34333.799 0.314 2 1 2 1 17078.513 17051.969 0.203 2 1 2 2 64501.198 64598.435 -0.383 2 2 1 1 8480.939 8466.016 0.162 2 2 1 2 32030.347 32072.039 -0.233 2 2 2 1 15905.800 15928.660 -0.181 2 2 2 2 106140.150 106055.080 0.261 *** LOG-LINEAR PARAMETERS *** * TABLE ABCD [or P(ABCD)] * effect beta exp(beta) main 10.7258 4.55E+0004 A 1 0.5250 1.6904 2 -0.5250 0.5916 B 1 0.1751 1.1913 2 -0.1751 0.8394 C 1 -0.1751 0.8394 2 0.1751 1.1913 D 1 -0.5250 0.5916 2 0.5250 1.6904 type 2 association (row=A column=B slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.2820 adj slab 0.2820 type 2 association (row=A column=C slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.2820 adj slab 0.2820 type 2 association (row=A column=D slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.2820 adj slab 0.2820 type 2 association (row=B column=C slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.2820 adj slab 0.2820 type 2 association (row=B column=D slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.2820 adj slab 0.2820 type 2 association (row=C column=D slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.2820 adj slab 0.2820