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 (3c3) * 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) ass2(S,Y,5a,-2) } des [ 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 = 0.0000009864 X-squared = 100.9576 (0.3447) L-squared = 107.9497 (0.1903) Cressie-Read = 100.1253 (0.3664) Dissimilarity index = 0.0863 Degrees of freedom = 96 Log-likelihood = -6394.95841 Number of parameters = 47 (+1) Sample size = 1399.0 BIC(L-squared) = -587.4275 AIC(L-squared) = -84.0503 BIC(log-likelihood) = 13130.3619 AIC(log-likelihood) = 12883.9168 WARNING: no information is provided on identification of parameters *** FREQUENCIES *** S X Y observed estimated std. res. 1 1 1 44.000 37.801 1.008 1 1 2 4.000 6.386 -0.944 1 1 3 9.000 9.088 -0.029 1 1 4 7.000 5.259 0.759 1 1 5 6.000 5.225 0.339 1 1 6 7.000 9.539 -0.822 1 2 1 13.000 13.530 -0.144 1 2 2 30.000 26.184 0.746 1 2 3 20.000 18.809 0.275 1 2 4 8.000 11.503 -1.033 1 2 5 14.000 13.870 0.035 1 2 6 7.000 5.736 0.528 1 3 1 9.000 12.792 -1.060 1 3 2 23.000 22.167 0.177 1 3 3 17.000 15.671 0.336 1 3 4 17.000 13.617 0.917 1 3 5 3.000 4.223 -0.595 1 3 6 0.000 2.193 -1.481 1 4 1 16.000 15.828 0.043 1 4 2 17.000 21.237 -0.919 1 4 3 10.000 13.965 -1.061 1 4 4 20.000 18.457 0.359 1 4 5 2.000 3.422 -0.769 1 4 6 2.000 2.196 -0.132 1 5 1 5.000 4.979 0.009 1 5 2 4.000 7.851 -1.374 1 5 3 9.000 6.926 0.788 1 5 4 10.000 5.928 1.672 1 5 5 4.000 2.883 0.658 1 5 6 0.000 0.802 -0.896 1 6 1 3.000 3.148 -0.083 1 6 2 3.000 2.696 0.185 1 6 3 0.000 2.203 -1.484 1 6 4 1.000 1.712 -0.544 1 6 5 4.000 0.724 3.849 1 6 6 1.000 0.444 0.833 2 1 1 7.000 13.596 -1.789 2 1 2 4.000 2.548 0.910 2 1 3 5.000 5.281 -0.122 2 1 4 5.000 4.876 0.056 2 1 5 14.000 12.499 0.425 2 1 6 69.000 70.897 -0.225 2 2 1 5.000 4.756 0.112 2 2 2 7.000 10.207 -1.004 2 2 3 13.000 10.681 0.709 2 2 4 15.000 10.421 1.418 2 2 5 38.000 32.421 0.980 2 2 6 37.000 41.662 -0.722 2 3 1 6.000 4.135 0.917 2 3 2 7.000 7.947 -0.336 2 3 3 8.000 8.184 -0.064 2 3 4 10.000 11.346 -0.400 2 3 5 10.000 9.079 0.306 2 3 6 15.000 14.648 0.092 2 4 1 4.000 4.611 -0.285 2 4 2 12.000 6.862 1.961 2 4 3 5.000 6.573 -0.614 2 4 4 13.000 13.860 -0.231 2 4 5 6.000 6.631 -0.245 2 4 6 14.000 13.220 0.214 2 5 1 2.000 1.175 0.761 2 5 2 3.000 2.054 0.660 2 5 3 1.000 2.640 -1.009 2 5 4 1.000 3.605 -1.372 2 5 5 3.000 4.524 -0.717 2 5 6 5.000 3.910 0.551 2 6 1 0.000 0.577 -0.760 2 6 2 0.000 0.548 -0.740 2 6 3 1.000 0.653 0.430 2 6 4 1.000 0.809 0.212 2 6 5 1.000 0.883 0.125 2 6 6 3.000 1.684 1.015 3 1 1 8.000 8.066 -0.023 3 1 2 2.000 1.390 0.517 3 1 3 2.000 2.126 -0.086 3 1 4 1.000 1.345 -0.298 3 1 5 0.000 1.603 -1.266 3 1 6 4.000 3.634 0.192 3 2 1 5.000 3.301 0.935 3 2 2 5.000 6.516 -0.594 3 2 3 5.000 5.031 -0.014 3 2 4 5.000 3.364 0.892 3 2 5 5.000 4.864 0.062 3 2 6 3.000 2.499 0.317 3 3 1 8.000 5.080 1.295 3 3 2 10.000 8.980 0.340 3 3 3 7.000 6.822 0.068 3 3 4 4.000 6.483 -0.975 3 3 5 1.000 2.411 -0.909 3 3 6 1.000 1.555 -0.445 3 4 1 12.000 11.511 0.144 3 4 2 17.000 15.754 0.314 3 4 3 15.000 11.133 1.159 3 4 4 13.000 16.090 -0.770 3 4 5 2.000 3.577 -0.834 3 4 6 2.000 2.852 -0.504 3 5 1 12.000 12.358 -0.102 3 5 2 17.000 19.874 -0.645 3 5 3 19.000 18.842 0.036 3 5 4 18.000 17.636 0.087 3 5 5 10.000 10.285 -0.089 3 5 6 4.000 3.555 0.236 3 6 1 31.000 33.919 -0.501 3 6 2 29.000 29.630 -0.116 3 6 3 25.000 26.026 -0.201 3 6 4 24.000 22.117 0.400 3 6 5 12.000 11.217 0.234 3 6 6 12.000 8.551 1.179 4 1 1 4.000 3.537 0.246 4 1 2 1.000 0.676 0.394 4 1 3 2.000 1.506 0.403 4 1 4 0.000 1.520 -1.233 4 1 5 4.000 4.673 -0.311 4 1 6 37.000 32.930 0.709 4 2 1 0.000 1.413 -1.189 4 2 2 4.000 3.093 0.516 4 2 3 0.000 3.479 -1.865 4 2 4 1.000 3.712 -1.408 4 2 5 8.000 13.845 -1.571 4 2 6 25.000 22.104 0.616 4 3 1 1.000 1.993 -0.703 4 3 2 3.000 3.906 -0.458 4 3 3 3.000 4.323 -0.636 4 3 4 7.000 6.554 0.174 4 3 5 8.000 6.287 0.683 4 3 6 15.000 12.604 0.675 4 4 1 4.000 4.050 -0.025 4 4 2 4.000 6.147 -0.866 4 4 3 8.000 6.328 0.664 4 4 4 17.000 14.592 0.630 4 4 5 12.000 8.370 1.255 4 4 6 21.000 20.732 0.059 4 5 1 3.000 3.488 -0.261 4 5 2 12.000 6.221 2.317 4 5 3 8.000 8.592 -0.202 4 5 4 11.000 12.831 -0.511 4 5 5 20.000 19.307 0.158 4 5 6 20.000 20.733 -0.161 4 6 1 11.000 7.356 1.344 4 6 2 8.000 7.126 0.327 4 6 3 12.000 9.118 0.954 4 6 4 11.000 12.362 -0.387 4 6 5 12.000 16.176 -1.038 4 6 6 33.000 38.321 -0.860 *** LOG-LINEAR PARAMETERS *** * TABLE SXY [or P(SXY)] * effect beta exp(beta) main 1.8157 6.1454 S 1 0.0193 1.0195 2 -0.1671 0.8461 3 0.0734 1.0761 4 0.0744 1.0772 X 1 -0.1987 0.8198 2 0.2501 1.2841 3 0.0530 1.0545 4 0.3274 1.3873 5 -0.0279 0.9725 6 -0.4039 0.6677 Y 1 -1.6027 0.2013 2 -1.3914 0.2487 3 -0.8175 0.4415 4 -0.1013 0.9037 5 1.0850 2.9595 6 2.8278 16.9087 XY 1 1 0.8737 2.3957 1 2 -0.9088 0.4030 1 3 -0.3776 0.6855 1 4 -0.7066 0.4933 1 5 -0.0036 0.9964 1 6 1.1229 3.0738 2 1 -0.5473 0.5785 2 2 0.1086 1.1147 2 3 -0.0437 0.9573 2 4 -0.3174 0.7280 2 5 0.5791 1.7844 2 6 0.2208 1.2470 3 1 -0.2055 0.8142 3 2 0.3399 1.4048 3 3 0.1716 1.1872 3 4 0.2492 1.2829 3 5 -0.2122 0.8088 3 6 -0.3429 0.7097 4 1 -0.0176 0.9826 4 2 0.2720 1.3126 4 3 0.0314 1.0319 4 4 0.5283 1.6960 4 5 -0.4475 0.6392 4 6 -0.3665 0.6931 5 1 -0.3129 0.7313 5 2 0.1381 1.1481 5 3 0.1912 1.2107 5 4 0.2537 1.2888 5 5 0.2424 1.2743 5 6 -0.5125 0.5990 6 1 0.2097 1.2333 6 2 0.0503 1.0516 6 3 0.0271 1.0274 6 4 -0.0071 0.9929 6 5 -0.1581 0.8537 6 6 -0.1218 0.8853 type 2 association (row=S column=X) association 3.4556 row -0.4075 -0.5773 0.5811 0.4037 adj row -0.7574 -1.0732 1.0803 0.7504 column -0.4077 -0.3685 -0.2259 -0.0488 0.3105 0.7404 adj column -0.7579 -0.6850 -0.4199 -0.0907 0.5773 1.3763 type 2 association (row=S column=Y) association -7.8801 row 0.6695 0.3347 0.6054 0.2707 adj row -1.8793 -0.9397 -1.6994 -0.7598 column -0.4077 -0.3685 -0.2259 -0.0488 0.3105 0.7404 adj column -1.1446 -1.0344 -0.6341 -0.1370 0.8717 2.0783