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 * All 2-way interaction log-linear model * man 5 dim 2 2 2 2 2 lab A B C D E mode {A B C D E AB AC AD AE BC BD BE CD CE DE} dlk ste 2 ite 150000 nco data [ 12 19 1 7 3 19 3 17 10 5 3 7 7 23 8 28 7 39 11 34 14 51 15 90 6 25 7 35 18 136 32 308 ] *** STATISTICS *** Number of iterations = 7 Converge criterion = 0.0000002266 X-squared = 20.1363 (0.2141) L-squared = 20.3850 (0.2034) Cressie-Read = 20.0684 (0.2172) Dissimilarity index = 0.0369 Degrees of freedom = 16 Log-likelihood = -2653.14732 Number of parameters = 15 (+1) Sample size = 1000.0 BIC(L-squared) = -90.1391 AIC(L-squared) = -11.6150 BIC(log-likelihood) = 5409.9110 AIC(log-likelihood) = 5336.2946 Eigenvalues information matrix 3238.6893 2124.6802 1457.3478 896.7563 806.0882 742.7826 566.6005 508.5724 458.2903 391.5054 358.5535 272.1569 247.5932 198.5718 183.0180 *** FREQUENCIES *** A B C D E observed estimated std. res. 1 1 1 1 1 12.000 11.494 0.149 1 1 1 1 2 19.000 17.832 0.277 1 1 1 2 1 1.000 4.162 -1.550 1 1 1 2 2 7.000 8.366 -0.472 1 1 2 1 1 3.000 5.683 -1.126 1 1 2 1 2 19.000 16.364 0.652 1 1 2 2 1 3.000 3.615 -0.323 1 1 2 2 2 17.000 13.484 0.958 1 2 1 1 1 10.000 4.983 2.248 1 2 1 1 2 5.000 8.812 -1.284 1 2 1 2 1 3.000 2.538 0.290 1 2 1 2 2 7.000 5.814 0.492 1 2 2 1 1 7.000 7.667 -0.241 1 2 2 1 2 23.000 25.166 -0.432 1 2 2 2 1 8.000 6.858 0.436 1 2 2 2 2 28.000 29.163 -0.215 2 1 1 1 1 7.000 11.079 -1.225 2 1 1 1 2 39.000 35.375 0.610 2 1 1 2 1 11.000 8.117 1.012 2 1 1 2 2 34.000 33.576 0.073 2 1 2 1 1 14.000 9.555 1.438 2 1 2 1 2 51.000 56.619 -0.747 2 1 2 2 1 15.000 12.295 0.771 2 1 2 2 2 90.000 94.385 -0.451 2 2 1 1 1 6.000 7.204 -0.449 2 2 1 1 2 25.000 26.222 -0.239 2 2 1 2 1 7.000 7.423 -0.155 2 2 1 2 2 35.000 35.003 -0.001 2 2 2 1 1 18.000 19.335 -0.304 2 2 2 1 2 136.000 130.610 0.472 2 2 2 2 1 32.000 34.991 -0.506 2 2 2 2 2 308.000 306.209 0.102 *** LOG-LINEAR PARAMETERS *** * TABLE ABCDE [or P(ABCDE)] * effect beta std err z-value exp(beta) Wald df prob main 2.7241 15.2422 A 1 -0.5787 0.0532 -10.869 0.5607 2 0.5787 1.7836 118.14 1 0.000 B 1 -0.0853 0.0538 -1.586 0.9183 2 0.0853 1.0890 2.51 1 0.113 C 1 -0.3661 0.0545 -6.721 0.6934 2 0.3661 1.4422 45.18 1 0.000 D 1 0.0409 0.0532 0.769 1.0418 2 -0.0409 0.9599 0.59 1 0.442 E 1 -0.6521 0.0523 -12.474 0.5210 2 0.6521 1.9195 155.59 1 0.000 AB 1 1 0.1014 0.0454 2.233 1.1067 1 2 -0.1014 0.9036 2 1 -0.1014 0.9036 2 2 0.1014 1.1067 4.98 1 0.026 AC 1 1 0.1391 0.0485 2.867 1.1492 1 2 -0.1391 0.8702 2 1 -0.1391 0.8702 2 2 0.1391 1.1492 8.22 1 0.004 BC 1 1 0.2838 0.0401 7.080 1.3282 1 2 -0.2838 0.7529 2 1 -0.2838 0.7529 2 2 0.2838 1.3282 50.13 1 0.000 AD 1 1 0.1762 0.0439 4.010 1.1926 1 2 -0.1762 0.8385 2 1 -0.1762 0.8385 2 2 0.1762 1.1926 16.08 1 0.000 BD 1 1 0.0853 0.0358 2.381 1.0890 1 2 -0.0853 0.9183 2 1 -0.0853 0.9183 2 2 0.0853 1.0890 5.67 1 0.017 CD 1 1 0.1408 0.0404 3.484 1.1512 1 2 -0.1408 0.8687 2 1 -0.1408 0.8687 2 2 0.1408 1.1512 12.14 1 0.000 AE 1 1 0.1804 0.0518 3.484 1.1977 1 2 -0.1804 0.8349 2 1 -0.1804 0.8349 2 2 0.1804 1.1977 12.14 1 0.000 BE 1 1 0.0327 0.0475 0.690 1.0333 1 2 -0.0327 0.9678 2 1 -0.0327 0.9678 2 2 0.0327 1.0333 0.48 1 0.490 CE 1 1 0.1546 0.0499 3.095 1.1672 1 2 -0.1546 0.8568 2 1 -0.1546 0.8568 2 2 0.1546 1.1672 9.58 1 0.002 DE 1 1 0.0647 0.0457 1.417 1.0669 1 2 -0.0647 0.9373 2 1 -0.0647 0.9373 2 2 0.0647 1.0669 2.01 1 0.157