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-linear models using 4 variables: (HLX,HLY,XY) * man 4 dim 2 2 6 6 lab L H X Y mod {L H X Y HL HY LX XY HLX HLY} 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 = 11 Converge criterion = 0.0000006505 X-squared = 85.4302 (0.1924) L-squared = 92.6232 (0.0818) Cressie-Read = 85.5753 (0.1895) Dissimilarity index = 0.0807 Degrees of freedom = 75 Log-likelihood = -6387.29515 Number of parameters = 68 (+1) Sample size = 1399.0 BIC(L-squared) = -450.6403 AIC(L-squared) = -57.3768 BIC(log-likelihood) = 13267.1492 AIC(log-likelihood) = 12910.5903 Eigenvalues information matrix 4033.5007 3474.0159 2939.5227 2214.1956 1576.3126 1266.8303 1167.0127 938.6459 675.2346 582.7007 487.7385 451.0448 388.2620 376.5438 370.9189 356.0939 332.5867 329.8001 304.0882 297.9140 290.1104 286.9089 277.9476 259.9307 255.1200 237.3248 232.2291 217.3892 207.9889 198.5355 188.1177 176.8214 170.1559 169.1517 165.9543 160.3684 156.5583 148.7312 141.8140 134.5760 132.9436 131.0098 126.1798 122.4333 121.4829 109.5392 108.0722 99.9010 90.9216 82.6920 72.0056 69.1056 49.3820 41.9560 40.7283 37.0325 35.4669 33.6585 31.8703 30.6966 29.0895 26.6863 24.5196 21.6752 20.1572 19.5850 15.9894 12.9443 *** FREQUENCIES *** L H X Y observed estimated std. res. 1 1 1 1 44.000 40.740 0.511 1 1 1 2 4.000 6.431 -0.959 1 1 1 3 9.000 9.584 -0.189 1 1 1 4 7.000 6.220 0.313 1 1 1 5 6.000 5.838 0.067 1 1 1 6 7.000 8.186 -0.415 1 1 2 1 13.000 14.019 -0.272 1 1 2 2 30.000 25.431 0.906 1 1 2 3 20.000 19.087 0.209 1 1 2 4 8.000 13.231 -1.438 1 1 2 5 14.000 15.272 -0.325 1 1 2 6 7.000 4.961 0.916 1 1 3 1 9.000 12.674 -1.032 1 1 3 2 23.000 20.571 0.536 1 1 3 3 17.000 15.010 0.514 1 1 3 4 17.000 14.915 0.540 1 1 3 5 3.000 4.254 -0.608 1 1 3 6 0.000 1.577 -1.256 1 1 4 1 16.000 14.168 0.487 1 1 4 2 17.000 17.891 -0.211 1 1 4 3 10.000 11.974 -0.571 1 1 4 4 20.000 18.577 0.330 1 1 4 5 2.000 3.084 -0.617 1 1 4 6 2.000 1.305 0.609 1 1 5 1 5.000 5.136 -0.060 1 1 5 2 4.000 7.900 -1.388 1 1 5 3 9.000 7.075 0.724 1 1 5 4 10.000 7.700 0.829 1 1 5 5 4.000 3.575 0.225 1 1 5 6 0.000 0.614 -0.783 1 1 6 1 3.000 3.263 -0.145 1 1 6 2 3.000 2.776 0.134 1 1 6 3 0.000 2.270 -1.507 1 1 6 4 1.000 2.356 -0.883 1 1 6 5 4.000 0.977 3.059 1 1 6 6 1.000 0.358 1.072 1 2 1 1 7.000 10.885 -1.178 1 2 1 2 4.000 2.605 0.864 1 2 1 3 5.000 4.899 0.046 1 2 1 4 5.000 4.465 0.253 1 2 1 5 14.000 12.886 0.310 1 2 1 6 69.000 68.259 0.090 1 2 2 1 5.000 3.975 0.514 1 2 2 2 7.000 10.932 -1.189 1 2 2 3 13.000 10.352 0.823 1 2 2 4 15.000 10.078 1.550 1 2 2 5 38.000 35.770 0.373 1 2 2 6 37.000 43.893 -1.040 1 2 3 1 6.000 3.603 1.263 1 2 3 2 7.000 8.866 -0.627 1 2 3 3 8.000 8.162 -0.057 1 2 3 4 10.000 11.391 -0.412 1 2 3 5 10.000 9.989 0.004 1 2 3 6 15.000 13.989 0.270 1 2 4 1 4.000 4.243 -0.118 1 2 4 2 12.000 8.125 1.360 1 2 4 3 5.000 6.860 -0.710 1 2 4 4 13.000 14.948 -0.504 1 2 4 5 6.000 7.631 -0.590 1 2 4 6 14.000 12.193 0.517 1 2 5 1 2.000 0.770 1.401 1 2 5 2 3.000 1.796 0.898 1 2 5 3 1.000 2.030 -0.723 1 2 5 4 1.000 3.103 -1.194 1 2 5 5 3.000 4.429 -0.679 1 2 5 6 5.000 2.872 1.256 1 2 6 1 0.000 0.523 -0.724 1 2 6 2 0.000 0.675 -0.822 1 2 6 3 1.000 0.697 0.363 1 2 6 4 1.000 1.016 -0.015 1 2 6 5 1.000 1.295 -0.259 1 2 6 6 3.000 1.794 0.900 2 1 1 1 8.000 7.605 0.143 2 1 1 2 2.000 1.186 0.747 2 1 1 3 2.000 2.013 -0.009 2 1 1 4 1.000 1.065 -0.063 2 1 1 5 0.000 1.140 -1.068 2 1 1 6 4.000 3.990 0.005 2 1 2 1 5.000 3.860 0.580 2 1 2 2 5.000 6.920 -0.730 2 1 2 3 5.000 5.913 -0.376 2 1 2 4 5.000 3.342 0.907 2 1 2 5 5.000 4.398 0.287 2 1 2 6 3.000 3.566 -0.300 2 1 3 1 8.000 5.447 1.094 2 1 3 2 10.000 8.735 0.428 2 1 3 3 7.000 7.257 -0.095 2 1 3 4 4.000 5.880 -0.775 2 1 3 5 1.000 1.912 -0.659 2 1 3 6 1.000 1.769 -0.578 2 1 4 1 12.000 12.526 -0.149 2 1 4 2 17.000 15.631 0.346 2 1 4 3 15.000 11.911 0.895 2 1 4 4 13.000 15.069 -0.533 2 1 4 5 2.000 2.852 -0.505 2 1 4 6 2.000 3.011 -0.583 2 1 5 1 12.000 12.336 -0.096 2 1 5 2 17.000 18.750 -0.404 2 1 5 3 19.000 19.117 -0.027 2 1 5 4 18.000 16.968 0.251 2 1 5 5 10.000 8.980 0.340 2 1 5 6 4.000 3.848 0.077 2 1 6 1 31.000 34.226 -0.551 2 1 6 2 29.000 28.778 0.041 2 1 6 3 25.000 26.789 -0.346 2 1 6 4 24.000 22.675 0.278 2 1 6 5 12.000 10.718 0.392 2 1 6 6 12.000 9.814 0.698 2 2 1 1 4.000 3.771 0.118 2 2 1 2 1.000 0.778 0.252 2 2 1 3 2.000 1.504 0.404 2 2 1 4 0.000 1.250 -1.118 2 2 1 5 4.000 4.135 -0.067 2 2 1 6 37.000 36.563 0.072 2 2 2 1 0.000 1.147 -1.071 2 2 2 2 4.000 2.718 0.777 2 2 2 3 0.000 2.648 -1.627 2 2 2 4 1.000 2.349 -0.880 2 2 2 5 8.000 9.559 -0.504 2 2 2 6 25.000 19.580 1.225 2 2 3 1 1.000 2.276 -0.846 2 2 3 2 3.000 4.828 -0.832 2 2 3 3 3.000 4.571 -0.735 2 2 3 4 7.000 5.814 0.492 2 2 3 5 8.000 5.846 0.891 2 2 3 6 15.000 13.665 0.361 2 2 4 1 4.000 5.062 -0.472 2 2 4 2 4.000 8.353 -1.506 2 2 4 3 8.000 7.255 0.277 2 2 4 4 17.000 14.406 0.683 2 2 4 5 12.000 8.433 1.228 2 2 4 6 21.000 22.491 -0.314 2 2 5 1 3.000 3.758 -0.391 2 2 5 2 12.000 7.553 1.618 2 2 5 3 8.000 8.778 -0.263 2 2 5 4 11.000 12.229 -0.351 2 2 5 5 20.000 20.016 -0.004 2 2 5 6 20.000 21.666 -0.358 2 2 6 1 11.000 6.987 1.518 2 2 6 2 8.000 7.770 0.083 2 2 6 3 12.000 8.244 1.308 2 2 6 4 11.000 10.953 0.014 2 2 6 5 12.000 16.011 -1.002 2 2 6 6 33.000 37.035 -0.663 *** LOG-LINEAR PARAMETERS *** * TABLE LHXY [or P(LHXY)] * effect beta std err z-value exp(beta) Wald df prob main 1.8045 6.0770 L 1 -0.0743 0.0392 -1.895 0.9284 2 0.0743 1.0771 3.59 1 0.058 H 1 0.0491 0.0391 1.255 1.0504 2 -0.0491 0.9521 1.58 1 0.209 X 1 -0.2239 0.0929 -2.409 0.7994 2 0.2260 0.0732 3.085 1.2535 3 0.0582 0.0740 0.787 1.0599 4 0.3327 0.0667 4.987 1.3947 5 -0.0521 0.0824 -0.632 0.9492 6 -0.3409 0.7112 39.08 5 0.000 Y 1 -0.1059 0.0793 -1.336 0.8995 2 0.0181 0.0753 0.241 1.0183 3 0.0211 0.0715 0.295 1.0213 4 0.0760 0.0710 1.071 1.0790 5 -0.0650 0.0746 -0.871 0.9371 6 0.0556 1.0572 3.55 5 0.616 LH 1 1 0.0480 0.0402 1.195 1.0492 1 2 -0.0480 0.9531 2 1 -0.0480 0.9531 2 2 0.0480 1.0492 1.43 1 0.232 LX 1 1 0.7213 0.0795 9.071 2.0572 1 2 0.6699 0.0698 9.600 1.9541 1 3 0.3627 0.0722 5.024 1.4372 1 4 0.0234 0.0645 0.363 1.0237 1 5 -0.5786 0.0814 -7.107 0.5607 1 6 -1.1988 0.3016 2 1 -0.7213 0.4861 2 2 -0.6699 0.5118 2 3 -0.3627 0.6958 2 4 -0.0234 0.9769 2 5 0.5786 1.7835 2 6 1.1988 3.3160 274.13 5 0.000 HX 1 1 -0.1297 0.0900 -1.442 0.8783 1 2 -0.0165 0.0773 -0.214 0.9836 1 3 -0.1025 0.0794 -1.291 0.9026 1 4 -0.1072 0.0703 -1.523 0.8984 1 5 0.1364 0.0870 1.567 1.1461 1 6 0.2196 1.2455 2 1 0.1297 1.1385 2 2 0.0165 1.0167 2 3 0.1025 1.1080 2 4 0.1072 1.1131 2 5 -0.1364 0.8725 2 6 -0.2196 0.8029 9.33 5 0.097 LY 1 1 0.0376 0.0869 0.432 1.0383 1 2 0.0777 0.0781 0.995 1.0808 1 3 0.0382 0.0798 0.479 1.0389 1 4 0.1124 0.0750 1.499 1.1190 1 5 0.0455 0.0837 0.543 1.0465 1 6 -0.3113 0.7325 2 1 -0.0376 0.9631 2 2 -0.0777 0.9253 2 3 -0.0382 0.9625 2 4 -0.1124 0.8937 2 5 -0.0455 0.9556 2 6 0.3113 1.3653 13.54 5 0.019 HY 1 1 0.5860 0.0763 7.677 1.7967 1 2 0.4120 0.0690 5.973 1.5099 1 3 0.3212 0.0694 4.628 1.3788 1 4 0.1236 0.0658 1.880 1.1316 1 5 -0.4395 0.0712 -6.175 0.6444 1 6 -1.0034 0.3666 2 1 -0.5860 0.5566 2 2 -0.4120 0.6623 2 3 -0.3212 0.7253 2 4 -0.1236 0.8837 2 5 0.4395 1.5519 2 6 1.0034 2.7276 267.52 5 0.000 XY 1 1 0.8879 0.1438 6.172 2.4300 1 2 -0.9142 0.2308 -3.961 0.4008 1 3 -0.3625 0.1922 -1.886 0.6959 1 4 -0.7542 0.2149 -3.510 0.4704 1 5 -0.0479 0.1787 -0.268 0.9533 1 6 1.1909 3.2899 2 1 -0.5476 0.1721 -3.183 0.5783 2 2 0.0919 0.1393 0.660 1.0962 2 3 -0.0423 0.1448 -0.292 0.9586 2 4 -0.3681 0.1567 -2.349 0.6920 2 5 0.5450 0.1316 4.141 1.7246 2 6 0.3212 1.3788 3 1 -0.1722 0.1695 -1.016 0.8419 3 2 0.3561 0.1414 2.518 1.4278 3 3 0.1937 0.1475 1.313 1.2137 3 4 0.2280 0.1438 1.586 1.2561 3 5 -0.2570 0.1741 -1.476 0.7734 3 6 -0.3486 0.7057 4 1 0.0302 0.1449 0.208 1.0306 4 2 0.3075 0.1314 2.341 1.3600 4 3 0.0586 0.1395 0.420 1.0604 4 4 0.5385 0.1219 4.418 1.7134 4 5 -0.4875 0.1700 -2.867 0.6142 4 6 -0.4472 0.6394 5 1 -0.3436 0.1762 -1.950 0.7092 5 2 0.1310 0.1509 0.868 1.1399 5 3 0.1733 0.1484 1.168 1.1893 5 4 0.2987 0.1447 2.065 1.3481 5 5 0.3010 0.1526 1.973 1.3513 5 6 -0.5605 0.5709 6 1 0.1453 1.1564 6 2 0.0278 1.0282 6 3 -0.0208 0.9794 6 4 0.0571 1.0588 6 5 -0.0536 0.9478 6 6 -0.1558 0.8557 185.71 25 0.000 LHX 1 1 1 0.0588 0.0777 0.756 1.0605 1 1 2 -0.0842 0.0691 -1.218 0.9193 1 1 3 0.0005 0.0718 0.007 1.0005 1 1 4 -0.0209 0.0640 -0.327 0.9793 1 1 5 0.0814 0.0809 1.005 1.0848 1 1 6 -0.0356 0.9651 1 2 1 -0.0588 0.9429 1 2 2 0.0842 1.0878 1 2 3 -0.0005 0.9995 1 2 4 0.0209 1.0211 1 2 5 -0.0814 0.9219 1 2 6 0.0356 1.0362 2 1 1 -0.0588 0.9429 2 1 2 0.0842 1.0878 2 1 3 -0.0005 0.9995 2 1 4 0.0209 1.0211 2 1 5 -0.0814 0.9219 2 1 6 0.0356 1.0362 2 2 1 0.0588 1.0605 2 2 2 -0.0842 0.9193 2 2 3 0.0005 1.0005 2 2 4 -0.0209 0.9793 2 2 5 0.0814 1.0848 2 2 6 -0.0356 0.9651 2.91 5 0.714 LHY 1 1 1 0.0478 0.0757 0.632 1.0490 1 1 2 0.0136 0.0686 0.199 1.0137 1 1 3 -0.0118 0.0691 -0.170 0.9883 1 1 4 0.0160 0.0652 0.246 1.0162 1 1 5 0.0175 0.0707 0.247 1.0176 1 1 6 -0.0832 0.9202 1 2 1 -0.0478 0.9533 1 2 2 -0.0136 0.9865 1 2 3 0.0118 1.0118 1 2 4 -0.0160 0.9841 1 2 5 -0.0175 0.9827 1 2 6 0.0832 1.0867 2 1 1 -0.0478 0.9533 2 1 2 -0.0136 0.9865 2 1 3 0.0118 1.0118 2 1 4 -0.0160 0.9841 2 1 5 -0.0175 0.9827 2 1 6 0.0832 1.0867 2 2 1 0.0478 1.0490 2 2 2 0.0136 1.0137 2 2 3 -0.0118 0.9883 2 2 4 0.0160 1.0162 2 2 5 0.0175 1.0176 2 2 6 -0.0832 0.9202 1.46 5 0.918