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 *** * Olzak & Wickens (1983) The interpretation of detection data * through direct multivariate frequency analysis. * Psych Bulletin, 93, 574-585. * * Subject B: Log-multiplicative model, graph 3 (c) w/ restrictions * man 3 dim 4 6 6 lab S X Y mod {S X Y XY ass2(S,X,5a) ass2(S,Y,5a) } ass_equ [ 1 2 3 2 ] nco dat [ 69 6 1 1 0 0 34 20 10 3 1 0 43 24 13 9 1 0 78 40 20 6 0 1 32 38 17 5 4 0 5 14 3 2 0 0 10 5 2 11 16 28 8 5 11 43 27 38 9 6 7 28 32 45 8 6 14 19 23 22 4 5 7 6 18 18 0 1 2 3 5 8 4 1 0 0 0 0 5 3 2 1 0 0 8 6 3 1 0 0 36 25 18 3 1 0 83 69 26 6 1 0 127 50 12 7 2 0 5 0 1 4 4 9 0 1 3 6 9 27 2 3 2 11 27 20 9 12 11 10 23 31 16 7 5 19 33 40 21 14 13 20 21 61 ] *** STATISTICS *** Number of iterations = 173 Converge criterion = 0.0000009365 X-squared = 130.9948 (0.0085) L-squared = 131.3922 (0.0080) Cressie-Read = 127.9652 (0.0136) Dissimilarity index = 0.0814 Degrees of freedom = 95 Log-likelihood = -8622.63009 Number of parameters = 48 (+1) Sample size = 2000.0 BIC(L-squared) = -590.6935 AIC(L-squared) = -58.6078 BIC(log-likelihood) = 17610.1035 AIC(log-likelihood) = 17341.2602 WARNING: no information is provided on identification of parameters *** FREQUENCIES *** S X Y observed estimated std. res. 1 1 1 69.000 64.008 0.624 1 1 2 6.000 8.214 -0.773 1 1 3 1.000 2.023 -0.719 1 1 4 1.000 2.631 -1.006 1 1 5 0.000 0.569 -0.755 1 1 6 0.000 0.099 -0.314 1 2 1 34.000 33.637 0.063 1 2 2 20.000 19.548 0.102 1 2 3 10.000 12.984 -0.828 1 2 4 3.000 8.637 -1.918 1 2 5 1.000 1.043 -0.043 1 2 6 0.000 0.172 -0.414 1 3 1 43.000 41.302 0.264 1 3 2 24.000 24.532 -0.107 1 3 3 13.000 11.754 0.363 1 3 4 9.000 7.597 0.509 1 3 5 1.000 1.607 -0.479 1 3 6 0.000 0.162 -0.402 1 4 1 78.000 67.431 1.287 1 4 2 40.000 40.603 -0.095 1 4 3 20.000 23.546 -0.731 1 4 4 6.000 4.810 0.542 1 4 5 0.000 1.023 -1.012 1 4 6 1.000 0.107 2.727 1 5 1 32.000 40.887 -1.390 1 5 2 38.000 34.625 0.574 1 5 3 17.000 12.731 1.197 1 5 4 5.000 3.010 1.147 1 5 5 4.000 0.813 3.533 1 5 6 0.000 0.076 -0.275 1 6 1 5.000 17.005 -2.911 1 6 2 14.000 8.569 1.855 1 6 3 3.000 2.769 0.139 1 6 4 2.000 1.238 0.685 1 6 5 0.000 0.199 -0.446 1 6 6 0.000 0.044 -0.209 2 1 1 10.000 13.342 -0.915 2 1 2 5.000 2.290 1.790 2 1 3 2.000 1.407 0.500 2 1 4 11.000 10.374 0.194 2 1 5 16.000 15.094 0.233 2 1 6 28.000 28.101 -0.019 2 2 1 8.000 6.862 0.435 2 2 2 5.000 5.334 -0.145 2 2 3 11.000 8.837 0.728 2 2 4 43.000 33.324 1.676 2 2 5 27.000 27.069 -0.013 2 2 6 38.000 47.752 -1.411 2 3 1 9.000 7.873 0.402 2 3 2 6.000 6.256 -0.102 2 3 3 7.000 7.475 -0.174 2 3 4 28.000 27.392 0.116 2 3 5 32.000 38.947 -1.113 2 3 6 45.000 42.032 0.458 2 4 1 8.000 11.302 -0.982 2 4 2 6.000 9.104 -1.029 2 4 3 14.000 13.167 0.229 2 4 4 19.000 15.250 0.960 2 4 5 23.000 21.810 0.255 2 4 6 22.000 24.524 -0.510 2 5 1 4.000 5.950 -0.799 2 5 2 5.000 6.740 -0.670 2 5 3 7.000 6.181 0.329 2 5 4 6.000 8.286 -0.794 2 5 5 18.000 15.053 0.760 2 5 6 18.000 15.016 0.770 2 6 1 0.000 2.075 -1.441 2 6 2 1.000 1.399 -0.337 2 6 3 2.000 1.128 0.822 2 6 4 3.000 2.857 0.085 2 6 5 5.000 3.089 1.088 2 6 6 8.000 7.302 0.258 3 1 1 4.000 7.550 -1.292 3 1 2 1.000 0.957 0.044 3 1 3 0.000 0.227 -0.476 3 1 4 0.000 0.273 -0.523 3 1 5 0.000 0.054 -0.233 3 1 6 0.000 0.009 -0.092 3 2 1 5.000 4.680 0.148 3 2 2 3.000 2.686 0.192 3 2 3 2.000 1.715 0.218 3 2 4 1.000 1.058 -0.057 3 2 5 0.000 0.118 -0.343 3 2 6 0.000 0.017 -0.132 3 3 1 8.000 9.656 -0.533 3 3 2 6.000 5.664 0.141 3 3 3 3.000 2.609 0.242 3 3 4 1.000 1.564 -0.451 3 3 5 0.000 0.305 -0.552 3 3 6 0.000 0.028 -0.166 3 4 1 36.000 42.230 -0.959 3 4 2 25.000 25.111 -0.022 3 4 3 18.000 13.999 1.070 3 4 4 3.000 2.653 0.213 3 4 5 1.000 0.520 0.666 3 4 6 0.000 0.049 -0.222 3 5 1 83.000 75.564 0.855 3 5 2 69.000 63.190 0.731 3 5 3 26.000 22.335 0.776 3 5 4 6.000 4.900 0.497 3 5 5 1.000 1.219 -0.199 3 5 6 0.000 0.102 -0.320 3 6 1 127.000 120.951 0.550 3 6 2 50.000 60.185 -1.313 3 6 3 12.000 18.698 -1.549 3 6 4 7.000 7.753 -0.270 3 6 5 2.000 1.148 0.795 3 6 6 0.000 0.228 -0.478 4 1 1 5.000 3.100 1.079 4 1 2 0.000 0.539 -0.734 4 1 3 1.000 0.344 1.120 4 1 4 4.000 2.721 0.775 4 1 5 4.000 4.282 -0.136 4 1 6 9.000 8.791 0.070 4 2 1 0.000 1.821 -1.349 4 2 2 1.000 1.432 -0.361 4 2 3 3.000 2.464 0.341 4 2 4 6.000 9.981 -1.260 4 2 5 9.000 8.770 0.078 4 2 6 27.000 17.059 2.407 4 3 1 2.000 3.169 -0.657 4 3 2 3.000 2.549 0.283 4 3 3 2.000 3.162 -0.654 4 3 4 11.000 12.446 -0.410 4 3 5 27.000 19.141 1.796 4 3 6 20.000 22.779 -0.582 4 4 1 9.000 10.037 -0.327 4 4 2 12.000 8.182 1.335 4 4 3 11.000 12.288 -0.367 4 4 4 10.000 15.286 -1.352 4 4 5 23.000 23.647 -0.133 4 4 6 31.000 29.320 0.310 4 5 1 16.000 12.599 0.958 4 5 2 7.000 14.444 -1.959 4 5 3 5.000 13.754 -2.360 4 5 4 19.000 19.804 -0.181 4 5 5 33.000 38.914 -0.948 4 5 6 40.000 42.806 -0.429 4 6 1 21.000 12.969 2.230 4 6 2 14.000 8.847 1.732 4 6 3 13.000 7.405 2.056 4 6 4 20.000 20.152 -0.034 4 6 5 21.000 23.564 -0.528 4 6 6 61.000 61.426 -0.054 *** LOG-LINEAR PARAMETERS *** * TABLE SXY [or P(SXY)] * effect beta exp(beta) main 1.5320 4.6276 S 1 -0.2923 0.7465 2 0.6857 1.9851 3 -0.9869 0.3727 4 0.5936 1.8105 X 1 -0.9985 0.3684 2 -0.1967 0.8214 3 0.0994 1.1045 4 0.5410 1.7177 5 0.5711 1.7702 6 -0.0162 0.9839 Y 1 1.0785 2.9402 2 0.4779 1.6126 3 0.0642 1.0663 4 0.1947 1.2150 5 -0.5004 0.6063 6 -1.3148 0.2685 XY 1 1 0.8637 2.3720 1 2 -0.4435 0.6418 1 3 -0.9745 0.3774 1 4 0.0245 1.0248 1 5 0.1408 1.1512 1 6 0.3889 1.4754 2 1 -0.5178 0.5958 2 2 -0.3146 0.7301 2 3 0.1465 1.1577 2 4 0.4749 1.6079 2 5 0.0084 1.0084 2 6 0.2026 1.2246 3 1 -0.4086 0.6646 3 2 -0.1835 0.8323 3 3 -0.0491 0.9521 3 4 0.2506 1.2848 3 5 0.3439 1.4105 3 6 0.0467 1.0478 4 1 0.0199 1.0201 4 2 0.2586 1.2951 4 3 0.5839 1.7930 4 4 -0.2682 0.7648 4 5 -0.1690 0.8445 4 6 -0.4252 0.6537 5 1 -0.0934 0.9108 5 2 0.4863 1.6263 5 3 0.3559 1.4275 5 4 -0.3499 0.7048 5 5 -0.0115 0.9885 5 6 -0.3874 0.6788 6 1 0.1361 1.1458 6 2 0.1967 1.2174 6 3 -0.0627 0.9393 6 4 -0.1319 0.8764 6 5 -0.3126 0.7316 6 6 0.1743 1.1905 type 2 association (row=S column=X) association 3.3759 row -0.4121 -0.5517 0.6570 0.3068 adj row -0.7572 -1.0137 1.2072 0.5637 column -0.4327 -0.3869 -0.2431 0.0299 0.3297 0.7031 adj column -0.7950 -0.7109 -0.4467 0.0549 0.6058 1.2919 type 2 association (row=S column=Y) association 6.6292 row -0.4789 0.4798 -0.5203 0.5193 adj row -1.2330 1.2355 -1.3396 1.3372 column -0.4327 -0.3869 -0.2431 0.0299 0.3297 0.7031 adj column -1.1141 -0.9962 -0.6260 0.0769 0.8489 1.8103