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 *** * Wickens (1992) MLE of a multivariate guassian rating * model with excluded data. J Math Psych, 36, 213-234. * Subject A (Wickens & Olzak 1989) * * Log-multiplicative models: graph 3 (c) model (3c4) * with restrictions * X=low , Y=high man 3 dim 4 6 6 lab S X Y mod {S X Y XY ass2(S,X,5a,3) ass2(S,Y,5a,-2) } des [ 1 1 2 3 2 1 2 1 0 0 1 1 ] ass_equ [ 1 2 3 2 ] nco dat[ 44 4 9 7 6 7 13 30 20 8 14 7 9 23 17 17 3 0 16 17 10 20 2 2 5 4 9 10 4 0 3 3 0 1 4 1 7 4 5 5 14 69 5 7 13 15 38 37 6 7 8 10 10 15 4 12 5 13 6 14 2 3 1 1 3 5 0 0 1 1 1 3 8 2 2 1 0 4 5 5 5 5 5 3 8 10 7 4 1 1 12 17 15 13 2 2 12 17 19 18 10 4 31 29 25 24 12 12 4 1 2 0 4 37 0 4 0 1 8 25 1 3 3 7 8 15 4 4 8 17 12 21 3 12 8 11 20 20 11 8 12 11 12 33 ] *** STATISTICS *** Number of iterations = 129 Converge criterion = 0.0000009695 X-squared = 109.2440 (0.1862) L-squared = 111.1210 (0.1549) Cressie-Read = 105.9140 (0.2518) Dissimilarity index = 0.0863 Degrees of freedom = 97 Log-likelihood = -6396.54404 Number of parameters = 46 (+1) Sample size = 1399.0 BIC(L-squared) = -591.4998 AIC(L-squared) = -82.8790 BIC(log-likelihood) = 13126.2897 AIC(log-likelihood) = 12885.0881 WARNING: no information is provided on identification of parameters *** FREQUENCIES *** S X Y observed estimated std. res. 1 1 1 44.000 39.460 0.723 1 1 2 4.000 6.661 -1.031 1 1 3 9.000 9.526 -0.170 1 1 4 7.000 5.560 0.611 1 1 5 6.000 5.631 0.155 1 1 6 7.000 10.288 -1.025 1 2 1 13.000 14.008 -0.269 1 2 2 30.000 27.071 0.563 1 2 3 20.000 19.505 0.112 1 2 4 8.000 12.000 -1.155 1 2 5 14.000 14.678 -0.177 1 2 6 7.000 6.052 0.385 1 3 1 9.000 12.920 -1.091 1 3 2 23.000 22.321 0.144 1 3 3 17.000 15.732 0.320 1 3 4 17.000 13.646 0.908 1 3 5 3.000 4.232 -0.599 1 3 6 0.000 2.168 -1.472 1 4 1 16.000 15.487 0.130 1 4 2 17.000 20.683 -0.810 1 4 3 10.000 13.487 -0.949 1 4 4 20.000 17.670 0.554 1 4 5 2.000 3.236 -0.687 1 4 6 2.000 2.031 -0.022 1 5 1 5.000 4.531 0.220 1 5 2 4.000 7.101 -1.164 1 5 3 9.000 6.189 1.130 1 5 4 10.000 5.227 2.087 1 5 5 4.000 2.492 0.956 1 5 6 0.000 0.674 -0.821 1 6 1 3.000 2.552 0.281 1 6 2 3.000 2.173 0.561 1 6 3 0.000 1.758 -1.326 1 6 4 1.000 1.351 -0.302 1 6 5 4.000 0.562 4.588 1 6 6 1.000 0.335 1.149 2 1 1 7.000 12.438 -1.542 2 1 2 4.000 2.353 1.074 2 1 3 5.000 4.946 0.024 2 1 4 5.000 4.622 0.176 2 1 5 14.000 12.062 0.558 2 1 6 69.000 69.262 -0.031 2 2 1 5.000 4.415 0.278 2 2 2 7.000 9.563 -0.829 2 2 3 13.000 10.128 0.902 2 2 4 15.000 9.976 1.591 2 2 5 38.000 31.439 1.170 2 2 6 37.000 40.743 -0.586 2 3 1 6.000 4.073 0.955 2 3 2 7.000 7.885 -0.315 2 3 3 8.000 8.170 -0.059 2 3 4 10.000 11.344 -0.399 2 3 5 10.000 9.064 0.311 2 3 6 15.000 14.595 0.106 2 4 1 4.000 4.882 -0.399 2 4 2 12.000 7.307 1.736 2 4 3 5.000 7.003 -0.757 2 4 4 13.000 14.690 -0.441 2 4 5 6.000 6.931 -0.354 2 4 6 14.000 13.676 0.088 2 5 1 2.000 1.428 0.478 2 5 2 3.000 2.509 0.310 2 5 3 1.000 3.214 -1.235 2 5 4 1.000 4.346 -1.605 2 5 5 3.000 5.337 -1.011 2 5 6 5.000 4.538 0.217 2 6 1 0.000 0.804 -0.897 2 6 2 0.000 0.768 -0.876 2 6 3 1.000 0.913 0.091 2 6 4 1.000 1.123 -0.116 2 6 5 1.000 1.203 -0.185 2 6 6 3.000 2.255 0.496 3 1 1 8.000 7.801 0.071 3 1 2 2.000 1.347 0.563 3 1 3 2.000 2.079 -0.055 3 1 4 1.000 1.332 -0.288 3 1 5 0.000 1.628 -1.276 3 1 6 4.000 3.732 0.139 3 2 1 5.000 3.240 0.978 3 2 2 5.000 6.405 -0.555 3 2 3 5.000 4.981 0.009 3 2 4 5.000 3.364 0.892 3 2 5 5.000 4.964 0.016 3 2 6 3.000 2.569 0.269 3 3 1 8.000 5.080 1.295 3 3 2 10.000 8.978 0.341 3 3 3 7.000 6.830 0.065 3 3 4 4.000 6.504 -0.982 3 3 5 1.000 2.433 -0.919 3 3 6 1.000 1.564 -0.451 3 4 1 12.000 11.645 0.104 3 4 2 17.000 15.908 0.274 3 4 3 15.000 11.197 1.137 3 4 4 13.000 16.104 -0.773 3 4 5 2.000 3.558 -0.826 3 4 6 2.000 2.803 -0.480 3 5 1 12.000 12.548 -0.155 3 5 2 17.000 20.115 -0.695 3 5 3 19.000 18.922 0.018 3 5 4 18.000 17.546 0.108 3 5 5 10.000 10.089 -0.028 3 5 6 4.000 3.425 0.311 3 6 1 31.000 34.226 -0.551 3 6 2 29.000 29.817 -0.150 3 6 3 25.000 26.034 -0.203 3 6 4 24.000 21.968 0.434 3 6 5 12.000 11.014 0.297 3 6 6 12.000 8.244 1.308 4 1 1 4.000 3.300 0.385 4 1 2 1.000 0.639 0.452 4 1 3 2.000 1.449 0.458 4 1 4 0.000 1.486 -1.219 4 1 5 4.000 4.679 -0.314 4 1 6 37.000 33.719 0.565 4 2 1 0.000 1.337 -1.156 4 2 2 4.000 2.962 0.603 4 2 3 0.000 3.386 -1.840 4 2 4 1.000 3.661 -1.391 4 2 5 8.000 13.918 -1.586 4 2 6 25.000 22.636 0.497 4 3 1 1.000 1.927 -0.668 4 3 2 3.000 3.816 -0.418 4 3 3 3.000 4.268 -0.614 4 3 4 7.000 6.506 0.194 4 3 5 8.000 6.271 0.690 4 3 6 15.000 12.673 0.654 4 4 1 4.000 3.986 0.007 4 4 2 4.000 6.102 -0.851 4 4 3 8.000 6.313 0.671 4 4 4 17.000 14.536 0.646 4 4 5 12.000 8.275 1.295 4 4 6 21.000 20.490 0.113 4 5 1 3.000 3.493 -0.264 4 5 2 12.000 6.275 2.285 4 5 3 8.000 8.676 -0.230 4 5 4 11.000 12.881 -0.524 4 5 5 20.000 19.082 0.210 4 5 6 20.000 20.363 -0.080 4 6 1 11.000 7.418 1.315 4 6 2 8.000 7.243 0.281 4 6 3 12.000 9.296 0.887 4 6 4 11.000 12.558 -0.440 4 6 5 12.000 16.221 -1.048 4 6 6 33.000 38.166 -0.836 *** LOG-LINEAR PARAMETERS *** * TABLE SXY [or P(SXY)] * effect beta exp(beta) main 1.8185 6.1625 S 1 -0.0343 0.9663 2 -0.0954 0.9090 3 0.0677 1.0701 4 0.0620 1.0639 X 1 -0.2108 0.8099 2 0.2414 1.2730 3 0.0473 1.0484 4 0.3251 1.3842 5 -0.0180 0.9821 6 -0.3849 0.6805 Y 1 -1.6275 0.1964 2 -1.3987 0.2469 3 -0.8112 0.4443 4 -0.0914 0.9127 5 1.0893 2.9721 6 2.8395 17.1064 XY 1 1 0.8492 2.3377 1 2 -0.9306 0.3943 1 3 -0.3901 0.6770 1 4 -0.7071 0.4931 1 5 0.0179 1.0180 1 6 1.1608 3.1925 2 1 -0.5665 0.5675 2 2 0.0916 1.0959 2 3 -0.0534 0.9480 2 4 -0.3178 0.7278 2 5 0.5959 1.8146 2 6 0.2502 1.2843 3 1 -0.2089 0.8115 3 2 0.3370 1.4008 3 3 0.1701 1.1854 3 4 0.2492 1.2830 3 5 -0.2094 0.8110 3 6 -0.3380 0.7132 4 1 -0.0070 0.9930 4 2 0.2815 1.3251 4 3 0.0367 1.0374 4 4 0.5283 1.6960 4 5 -0.4571 0.6331 4 6 -0.3824 0.6822 5 1 -0.2928 0.7462 5 2 0.1557 1.1685 5 3 0.2010 1.2226 5 4 0.2536 1.2887 5 5 0.2248 1.2520 5 6 -0.5423 0.5814 6 1 0.2261 1.2537 6 2 0.0648 1.0670 6 3 0.0356 1.0362 6 4 -0.0061 0.9939 6 5 -0.1720 0.8420 6 6 -0.1484 0.8621 type 2 association (row=S column=X) association 3.3982 row -0.4963 -0.4963 0.5818 0.4109 adj row -0.9149 -0.9149 1.0725 0.7574 column -0.4111 -0.3683 -0.2234 -0.0465 0.3094 0.7400 adj column -0.7579 -0.6789 -0.4119 -0.0857 0.5703 1.3641 type 2 association (row=S column=Y) association -7.9294 row 0.6708 0.3354 0.6043 0.2689 adj row -1.8890 -0.9445 -1.7017 -0.7572 column -0.4111 -0.3683 -0.2234 -0.0465 0.3094 0.7400 adj column -1.1577 -1.0370 -0.6292 -0.1309 0.8711 2.0837