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/ more restrictions * man 3 dim 4 6 6 lab S X Y mod {S X Y XY ass2(S,X,5a) ass2(S,Y,5a,2) } des [ 1 2 1 2 ] 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 = 166 Converge criterion = 0.0000009879 X-squared = 134.6628 (0.0069) L-squared = 134.0226 (0.0076) Cressie-Read = 130.9876 (0.0123) Dissimilarity index = 0.0817 Degrees of freedom = 97 Log-likelihood = -8623.94527 Number of parameters = 46 (+1) Sample size = 2000.0 BIC(L-squared) = -603.2649 AIC(L-squared) = -59.9774 BIC(log-likelihood) = 17597.5320 AIC(log-likelihood) = 17339.8905 WARNING: no information is provided on identification of parameters *** FREQUENCIES *** S X Y observed estimated std. res. 1 1 1 69.000 64.570 0.551 1 1 2 6.000 8.282 -0.793 1 1 3 1.000 2.010 -0.712 1 1 4 1.000 2.506 -0.951 1 1 5 0.000 0.510 -0.714 1 1 6 0.000 0.086 -0.293 1 2 1 34.000 33.940 0.010 1 2 2 20.000 19.709 0.066 1 2 3 10.000 12.898 -0.807 1 2 4 3.000 8.233 -1.824 1 2 5 1.000 0.938 0.064 1 2 6 0.000 0.149 -0.387 1 3 1 43.000 41.614 0.215 1 3 2 24.000 24.680 -0.137 1 3 3 13.000 11.637 0.399 1 3 4 9.000 7.246 0.651 1 3 5 1.000 1.456 -0.378 1 3 6 0.000 0.143 -0.378 1 4 1 78.000 67.912 1.224 1 4 2 40.000 40.730 -0.114 1 4 3 20.000 23.145 -0.654 1 4 4 6.000 4.590 0.658 1 4 5 0.000 0.944 -0.972 1 4 6 1.000 0.099 2.868 1 5 1 32.000 41.131 -1.424 1 5 2 38.000 34.583 0.581 1 5 3 17.000 12.389 1.310 1 5 4 5.000 2.869 1.258 1 5 5 4.000 0.766 3.694 1 5 6 0.000 0.073 -0.270 1 6 1 5.000 17.359 -2.966 1 6 2 14.000 8.660 1.814 1 6 3 3.000 2.713 0.174 1 6 4 2.000 1.194 0.737 1 6 5 0.000 0.194 -0.441 1 6 6 0.000 0.044 -0.211 2 1 1 10.000 12.533 -0.715 2 1 2 5.000 2.165 1.927 2 1 3 2.000 1.376 0.532 2 1 4 11.000 10.329 0.209 2 1 5 16.000 15.197 0.206 2 1 6 28.000 28.864 -0.161 2 2 1 8.000 6.434 0.617 2 2 2 5.000 5.032 -0.014 2 2 3 11.000 8.623 0.809 2 2 4 43.000 33.140 1.713 2 2 5 27.000 27.280 -0.054 2 2 6 38.000 49.215 -1.599 2 3 1 9.000 7.311 0.625 2 3 2 6.000 5.839 0.067 2 3 3 7.000 7.210 -0.078 2 3 4 28.000 27.030 0.187 2 3 5 32.000 39.245 -1.156 2 3 6 45.000 43.704 0.196 2 4 1 8.000 10.351 -0.731 2 4 2 6.000 8.361 -0.816 2 4 3 14.000 12.441 0.442 2 4 4 19.000 14.854 1.076 2 4 5 23.000 22.085 0.195 2 4 6 22.000 26.148 -0.811 2 5 1 4.000 5.361 -0.588 2 5 2 5.000 6.071 -0.435 2 5 3 7.000 5.695 0.547 2 5 4 6.000 7.940 -0.688 2 5 5 18.000 15.322 0.684 2 5 6 18.000 16.449 0.383 2 6 1 0.000 1.867 -1.367 2 6 2 1.000 1.255 -0.227 2 6 3 2.000 1.029 0.957 2 6 4 3.000 2.728 0.165 2 6 5 5.000 3.203 1.004 2 6 6 8.000 8.310 -0.108 3 1 1 4.000 7.406 -1.251 3 1 2 1.000 0.950 0.051 3 1 3 0.000 0.231 -0.480 3 1 4 0.000 0.287 -0.536 3 1 5 0.000 0.059 -0.242 3 1 6 0.000 0.010 -0.099 3 2 1 5.000 4.585 0.194 3 2 2 3.000 2.662 0.207 3 2 3 2.000 1.742 0.195 3 2 4 1.000 1.112 -0.106 3 2 5 0.000 0.127 -0.356 3 2 6 0.000 0.020 -0.142 3 3 1 8.000 9.542 -0.499 3 3 2 6.000 5.659 0.143 3 3 3 3.000 2.668 0.203 3 3 4 1.000 1.662 -0.513 3 3 5 0.000 0.334 -0.578 3 3 6 0.000 0.033 -0.181 3 4 1 36.000 41.775 -0.893 3 4 2 25.000 25.055 -0.011 3 4 3 18.000 14.237 0.997 3 4 4 3.000 2.823 0.105 3 4 5 1.000 0.581 0.550 3 4 6 0.000 0.061 -0.246 3 5 1 83.000 75.032 0.920 3 5 2 69.000 63.087 0.744 3 5 3 26.000 22.601 0.715 3 5 4 6.000 5.233 0.335 3 5 5 1.000 1.398 -0.336 3 5 6 0.000 0.133 -0.364 3 6 1 127.000 120.216 0.619 3 6 2 50.000 59.976 -1.288 3 6 3 12.000 18.786 -1.566 3 6 4 7.000 8.271 -0.442 3 6 5 2.000 1.344 0.566 3 6 6 0.000 0.308 -0.555 4 1 1 5.000 3.491 0.807 4 1 2 0.000 0.603 -0.777 4 1 3 1.000 0.383 0.996 4 1 4 4.000 2.877 0.662 4 1 5 4.000 4.234 -0.114 4 1 6 9.000 8.041 0.338 4 2 1 0.000 2.041 -1.429 4 2 2 1.000 1.597 -0.472 4 2 3 3.000 2.736 0.160 4 2 4 6.000 10.515 -1.392 4 2 5 9.000 8.656 0.117 4 2 6 27.000 15.615 2.881 4 3 1 2.000 3.533 -0.816 4 3 2 3.000 2.822 0.106 4 3 3 2.000 3.484 -0.795 4 3 4 11.000 13.062 -0.571 4 3 5 27.000 18.965 1.845 4 3 6 20.000 21.120 -0.244 4 4 1 9.000 10.963 -0.593 4 4 2 12.000 8.855 1.057 4 4 3 11.000 13.176 -0.600 4 4 4 10.000 15.732 -1.445 4 4 5 23.000 23.390 -0.081 4 4 6 31.000 27.693 0.628 4 5 1 16.000 13.476 0.688 4 5 2 7.000 15.260 -2.114 4 5 3 5.000 14.315 -2.462 4 5 4 19.000 19.958 -0.214 4 5 5 33.000 38.514 -0.889 4 5 6 40.000 41.346 -0.209 4 6 1 21.000 13.558 2.021 4 6 2 14.000 9.109 1.620 4 6 3 13.000 7.472 2.022 4 6 4 20.000 19.807 0.043 4 6 5 21.000 23.258 -0.468 4 6 6 61.000 60.337 0.085 *** LOG-LINEAR PARAMETERS *** * TABLE SXY [or P(SXY)] * effect beta exp(beta) main 1.5403 4.6661 S 1 -0.3355 0.7150 2 0.6506 1.9168 3 -0.9338 0.3931 4 0.6187 1.8565 X 1 -1.0007 0.3676 2 -0.1994 0.8192 3 0.0993 1.1044 4 0.5406 1.7171 5 0.5709 1.7699 6 -0.0108 0.9893 Y 1 1.0713 2.9191 2 0.4702 1.6003 3 0.0608 1.0627 4 0.1912 1.2107 5 -0.5011 0.6059 6 -1.2924 0.2746 XY 1 1 0.8762 2.4018 1 2 -0.4275 0.6521 1 3 -0.9527 0.3857 1 4 0.0351 1.0357 1 5 0.1248 1.1329 1 6 0.3442 1.4108 2 1 -0.5066 0.6025 2 2 -0.3002 0.7407 2 3 0.1665 1.1812 2 4 0.4848 1.6239 2 5 -0.0063 0.9937 2 6 0.1617 1.1755 3 1 -0.4020 0.6690 3 2 -0.1745 0.8399 3 3 -0.0356 0.9651 3 4 0.2579 1.2942 3 5 0.3343 1.3969 3 6 0.0199 1.0201 4 1 0.0183 1.0184 4 2 0.2570 1.2930 4 3 0.5825 1.7905 4 4 -0.2682 0.7647 4 5 -0.1682 0.8452 4 6 -0.4213 0.6562 5 1 -0.1038 0.9014 5 2 0.4727 1.6044 5 3 0.3369 1.4006 5 4 -0.3588 0.6985 5 5 0.0021 1.0021 5 6 -0.3490 0.7054 6 1 0.1179 1.1251 6 2 0.1725 1.1883 6 3 -0.0976 0.9070 6 4 -0.1508 0.8600 6 5 -0.2866 0.7508 6 6 0.2446 1.2771 type 2 association (row=S column=X) association 3.3840 row -0.4024 -0.5561 0.6655 0.2930 adj row -0.7403 -1.0230 1.2243 0.5390 column -0.4337 -0.3884 -0.2420 0.0311 0.3319 0.7010 adj column -0.7978 -0.7145 -0.4451 0.0572 0.6105 1.2896 type 2 association (row=S column=Y) association 6.5745 row -0.5000 0.5000 -0.5000 0.5000 adj row -1.2820 1.2820 -1.2820 1.2820 column -0.4337 -0.3884 -0.2420 0.0311 0.3319 0.7010 adj column -1.1119 -0.9958 -0.6204 0.0797 0.8510 1.7975