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 (b) * man 3 dim 4 6 6 lab S X Y mod {S X Y XY ass2(S,X,-,7a) ass2(S,Y,-,7a) ass2(X,Y,-,7a)} ass_equ [ 1 2 4 1 3 4 2 3 4 ] ass_res [ 0 2 3 0 2 3 2 2 3 ] ass_phi [ 1 1 1 ] 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 = 3981 Converge criterion = 0.0000009978 X-squared = 683.0307 (0.0000) L-squared = 584.2940 (0.0000) Cressie-Read = 609.6586 (0.0000) Dissimilarity index = 0.1912 Degrees of freedom = 92 Log-likelihood = -8849.08095 Number of parameters = 51 (+1) Sample size = 2000.0 BIC(L-squared) = -114.9890 AIC(L-squared) = 400.2940 BIC(log-likelihood) = 18085.8079 AIC(log-likelihood) = 17800.1619 WARNING: no information is provided on identification of parameters *** FREQUENCIES *** S X Y observed estimated std. res. 1 1 1 69.000 37.550 5.132 1 1 2 6.000 4.934 0.480 1 1 3 1.000 1.400 -0.338 1 1 4 1.000 2.221 -0.819 1 1 5 0.000 0.575 -0.758 1 1 6 0.000 0.156 -0.396 1 2 1 34.000 20.351 3.025 1 2 2 20.000 12.252 2.213 1 2 3 10.000 9.595 0.131 1 2 4 3.000 8.088 -1.789 1 2 5 1.000 1.187 -0.172 1 2 6 0.000 0.308 -0.555 1 3 1 43.000 26.956 3.090 1 3 2 24.000 16.917 1.722 1 3 3 13.000 9.929 0.974 1 3 4 9.000 8.711 0.098 1 3 5 1.000 2.306 -0.860 1 3 6 0.000 0.371 -0.609 1 4 1 78.000 53.544 3.342 1 4 2 40.000 35.363 0.780 1 4 3 20.000 27.131 -1.369 1 4 4 6.000 8.766 -0.934 1 4 5 0.000 2.499 -1.581 1 4 6 1.000 0.432 0.863 1 5 1 32.000 39.629 -1.212 1 5 2 38.000 39.256 -0.200 1 5 3 17.000 22.266 -1.116 1 5 4 5.000 12.200 -2.061 1 5 5 4.000 5.224 -0.536 1 5 6 0.000 0.848 -0.921 1 6 1 5.000 38.742 -5.421 1 6 2 14.000 22.904 -1.860 1 6 3 3.000 11.270 -2.463 1 6 4 2.000 11.840 -2.860 1 6 5 0.000 3.074 -1.753 1 6 6 0.000 1.207 -1.099 2 1 1 10.000 15.945 -1.489 2 1 2 5.000 2.489 1.592 2 1 3 2.000 1.083 0.881 2 1 4 11.000 6.691 1.666 2 1 5 16.000 10.114 1.851 2 1 6 28.000 20.545 1.645 2 2 1 8.000 7.687 0.113 2 2 2 5.000 5.498 -0.212 2 2 3 11.000 6.601 1.712 2 2 4 43.000 21.679 4.579 2 2 5 27.000 18.569 1.957 2 2 6 38.000 35.936 0.344 2 3 1 9.000 8.386 0.212 2 3 2 6.000 6.252 -0.101 2 3 3 7.000 5.626 0.579 2 3 4 28.000 19.232 1.999 2 3 5 32.000 29.706 0.421 2 3 6 45.000 35.671 1.562 2 4 1 8.000 11.700 -1.082 2 4 2 6.000 9.179 -1.049 2 4 3 14.000 10.798 0.975 2 4 4 19.000 13.593 1.466 2 4 5 23.000 22.617 0.081 2 4 6 22.000 29.220 -1.336 2 5 1 4.000 4.613 -0.285 2 5 2 5.000 5.428 -0.184 2 5 3 7.000 4.720 1.049 2 5 4 6.000 10.077 -1.284 2 5 5 18.000 25.181 -1.431 2 5 6 18.000 30.514 -2.265 2 6 1 0.000 3.733 -1.932 2 6 2 1.000 2.621 -1.001 2 6 3 2.000 1.978 0.016 2 6 4 3.000 8.095 -1.791 2 6 5 5.000 12.263 -2.074 2 6 6 8.000 35.959 -4.662 3 1 1 4.000 15.181 -2.870 3 1 2 1.000 1.599 -0.474 3 1 3 0.000 0.262 -0.512 3 1 4 0.000 0.072 -0.269 3 1 5 0.000 0.002 -0.044 3 1 6 0.000 0.000 -0.006 3 2 1 5.000 9.564 -1.476 3 2 2 3.000 4.615 -0.752 3 2 3 2.000 2.086 -0.059 3 2 4 1.000 0.306 1.255 3 2 5 0.000 0.005 -0.068 3 2 6 0.000 0.000 -0.010 3 3 1 8.000 16.259 -2.048 3 3 2 6.000 8.177 -0.761 3 3 3 3.000 2.770 0.138 3 3 4 1.000 0.423 0.887 3 3 5 0.000 0.012 -0.108 3 3 6 0.000 0.000 -0.012 3 4 1 36.000 50.863 -2.084 3 4 2 25.000 26.922 -0.370 3 4 3 18.000 11.923 1.760 3 4 4 3.000 0.670 2.846 3 4 5 1.000 0.020 6.969 3 4 6 0.000 0.000 -0.016 3 5 1 83.000 84.607 -0.175 3 5 2 69.000 67.170 0.223 3 5 3 26.000 21.992 0.855 3 5 4 6.000 2.097 2.696 3 5 5 1.000 0.093 2.976 3 5 6 0.000 0.001 -0.034 3 6 1 127.000 105.477 2.096 3 6 2 50.000 49.975 0.004 3 6 3 12.000 14.194 -0.582 3 6 4 7.000 2.594 2.735 3 6 5 2.000 0.070 7.311 3 6 6 0.000 0.002 -0.045 4 1 1 5.000 19.324 -3.258 4 1 2 0.000 2.978 -1.726 4 1 3 1.000 1.255 -0.228 4 1 4 4.000 7.016 -1.139 4 1 5 4.000 9.309 -1.740 4 1 6 9.000 16.299 -1.808 4 2 1 0.000 9.397 -3.065 4 2 2 1.000 6.635 -2.188 4 2 3 3.000 7.719 -1.699 4 2 4 6.000 22.928 -3.535 4 2 5 9.000 17.239 -1.984 4 2 6 27.000 28.757 -0.328 4 3 1 2.000 10.399 -2.605 4 3 2 3.000 7.654 -1.682 4 3 3 2.000 6.674 -1.809 4 3 4 11.000 20.634 -2.121 4 3 5 27.000 27.977 -0.185 4 3 6 20.000 28.958 -1.665 4 4 1 9.000 14.893 -1.527 4 4 2 12.000 11.536 0.137 4 4 3 11.000 13.148 -0.592 4 4 4 10.000 14.970 -1.285 4 4 5 23.000 21.864 0.243 4 4 6 31.000 24.348 1.348 4 5 1 16.000 6.151 3.971 4 5 2 7.000 7.146 -0.055 4 5 3 5.000 6.022 -0.416 4 5 4 19.000 11.626 2.162 4 5 5 33.000 25.502 1.485 4 5 6 40.000 26.637 2.589 4 6 1 21.000 5.048 7.100 4 6 2 14.000 3.500 5.613 4 6 3 13.000 2.558 6.528 4 6 4 20.000 9.471 3.421 4 6 5 21.000 12.594 2.369 4 6 6 61.000 31.832 5.170 *** LOG-LINEAR PARAMETERS *** * TABLE SXY [or P(SXY)] * effect beta exp(beta) main 1.3867 4.0014 S 1 0.3847 1.4691 2 0.9146 2.4959 3 -2.3037 0.0999 4 1.0044 2.7302 X 1 -1.0101 0.3642 2 -0.2096 0.8109 3 0.0198 1.0200 4 0.4082 1.5040 5 0.5318 1.7020 6 0.2599 1.2969 Y 1 1.4451 4.2425 2 0.8139 2.2567 3 0.2860 1.3310 4 0.2499 1.2839 5 -0.8095 0.4451 6 -1.9855 0.1373 XY 1 1 3.8799 48.4174 1 2 2.2818 9.7948 1 3 1.0542 2.8696 1 4 -0.0267 0.9736 1 5 -2.3651 0.0939 1 6 -4.8240 0.0080 2 1 1.9613 7.1088 2 2 1.9266 6.8663 2 3 1.8165 6.1505 2 4 0.4294 1.5364 2 5 -2.0542 0.1282 2 6 -4.0797 0.0169 3 1 1.1748 3.2375 3 2 1.2500 3.4904 3 3 1.0214 2.7772 3 4 0.2147 1.2395 3 5 -0.9785 0.3759 3 6 -2.6825 0.0684 4 1 -0.0530 0.9484 4 2 0.1978 1.2187 4 3 0.5461 1.7266 4 4 -0.2760 0.7589 4 5 -0.1191 0.8877 4 6 -0.2959 0.7439 5 1 -3.1978 0.0409 5 2 -2.3197 0.0983 5 3 -1.7223 0.1786 5 4 -0.2626 0.7690 5 5 2.5754 13.1371 5 6 4.9271 137.9747 6 1 -3.7652 0.0232 6 2 -3.3366 0.0356 6 3 -2.7159 0.0661 6 4 -0.0788 0.9242 6 5 2.9415 18.9440 6 6 6.9550 1.05E+0003 type 2 association (row=S column=X slab=) association 1.0000 row -0.0867 0.4549 -0.7832 0.4149 adj row -0.0867 0.4549 -0.7832 0.4149 column 0.7152 0.5854 0.3702 -0.0215 -0.7199 -0.9296 adj column 0.7152 0.5854 0.3702 -0.0215 -0.7199 -0.9296 slab 1.6649 adj slab 1.6649 type 2 association (row=S column=Y slab=) association 1.0000 row -0.0867 0.4549 -0.7832 0.4149 adj row -0.0867 0.4549 -0.7832 0.4149 column -2.2527 -2.0618 -1.5879 -0.0797 1.8763 4.1058 adj column -2.2527 -2.0618 -1.5879 -0.0797 1.8763 4.1058 slab 1.6649 adj slab 1.6649 type 2 association (row=X column=Y slab=) association 1.0000 row 0.7152 0.5854 0.3702 -0.0215 -0.7199 -0.9296 adj row 0.7152 0.5854 0.3702 -0.0215 -0.7199 -0.9296 column -2.2527 -2.0618 -1.5879 -0.0797 1.8763 4.1058 adj column -2.2527 -2.0618 -1.5879 -0.0797 1.8763 4.1058 slab 1.6649 adj slab 1.6649