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 *** * Generated probabilities from RASCH with theta exp(1) * b2= -1.05; * b3= -.35; * b4= .35; * b5= 1.05; * b6= 1.75; * b7= .50; * b8= -.50; * b9= -.70; man 8 dim 2 2 2 2 2 2 2 2 lab A B C D E F G H mod { A B C D E F G H ass2(A,B,-,7a) ass2(A,C,-,7a) ass2(A,D,-,7a) ass2(A,E,-,7a) ass2(A,F,-,7a) ass2(A,G,-,7a) ass2(A,H,-,7a) ass2(B,C,-,7a) ass2(B,D,-,7a) ass2(B,E,-,7a) ass2(B,F,-,7a) ass2(B,G,-,7a) ass2(B,H,-,7a) ass2(C,D,-,7a) ass2(C,E,-,7a) ass2(C,F,-,7a) ass2(C,G,-,7a) ass2(C,H,-,7a) ass2(D,E,-,7a) ass2(D,F,-,7a) ass2(D,G,-,7a) ass2(D,H,-,7a) ass2(E,F,-,7a) ass2(E,G,-,7a) ass2(E,H,-,7a) ass2(F,G,-,7a) ass2(F,H,-,7a) ass2(G,H,-,7a) } } ass_equ [ 1 2 13 1 3 13 1 4 13 1 5 13 1 6 13 1 7 13 1 8 13 2 3 13 2 4 13 2 5 13 2 6 13 2 7 13 2 8 13 3 4 13 3 5 13 3 6 13 3 7 13 3 8 13 4 5 13 4 6 13 4 7 13 4 8 13 5 6 13 5 7 13 5 8 13 6 7 13 6 8 13 7 8 13 ] ass_res [ 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 0 0 3 ] ass_phi [ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ] nco dat gen8rasch_normal.dat *** STATISTICS *** Number of iterations = 8 Converge criterion = 0.0000001984 X-squared = 100.0209 (1.0000) L-squared = 99.7448 (1.0000) Cressie-Read = 99.9282 (1.0000) Dissimilarity index = 0.0041 Degrees of freedom = 246 Log-likelihood = -4833099.55775 Number of parameters = 9 (+1) Sample size = 1000000.0 BIC(L-squared) = -3298.8708 AIC(L-squared) = -392.2552 BIC(log-likelihood) = 9666323.4551 AIC(log-likelihood) = 9666217.1155 WARNING: no information is provided on identification of parameters *** FREQUENCIES *** A B C D E F G H observed estimated std. res. 1 1 1 1 1 1 1 1 21749.169 21168.969 3.988 1 1 1 1 1 1 1 2 2410.574 2435.626 -0.508 1 1 1 1 1 1 2 1 2944.282 2974.670 -0.557 1 1 1 1 1 1 2 2 505.163 509.517 -0.193 1 1 1 1 1 2 1 1 8003.388 8090.635 -0.970 1 1 1 1 1 2 1 2 1373.175 1385.806 -0.339 1 1 1 1 1 2 2 1 1677.200 1692.508 -0.372 1 1 1 1 1 2 2 2 432.877 431.578 0.063 1 1 1 1 2 1 1 1 27934.570 28214.452 -1.666 1 1 1 1 2 1 1 2 4792.851 4832.719 -0.573 1 1 1 1 2 1 2 1 5854.002 5902.278 -0.628 1 1 1 1 2 1 2 2 1510.888 1505.042 0.151 1 1 1 1 2 2 1 1 15912.826 16053.269 -1.108 1 1 1 1 2 2 1 2 4107.020 4093.478 0.212 1 1 1 1 2 2 2 1 5016.326 4999.431 0.239 1 1 1 1 2 2 2 2 1915.844 1897.835 0.413 1 1 1 2 1 1 1 1 13871.897 14024.510 -1.289 1 1 1 2 1 1 1 2 2380.059 2402.191 -0.452 1 1 1 2 1 1 2 1 2907.011 2933.836 -0.495 1 1 1 2 1 1 2 2 750.285 748.109 0.080 1 1 1 2 1 2 1 1 7902.076 7979.572 -0.868 1 1 1 2 1 2 1 2 2039.486 2034.738 0.105 1 1 1 2 1 2 2 1 2491.034 2485.059 0.120 1 1 1 2 1 2 2 2 951.380 943.354 0.261 1 1 1 2 2 1 1 1 27580.954 27827.143 -1.476 1 1 1 2 2 1 1 2 7118.506 7095.737 0.270 1 1 1 2 2 1 2 1 8694.562 8666.140 0.305 1 1 1 2 2 1 2 2 3320.642 3289.755 0.539 1 1 1 2 2 2 1 1 23634.270 23570.538 0.415 1 1 1 2 2 2 1 2 9026.441 8947.618 0.833 1 1 1 2 2 2 2 1 11024.920 10927.872 0.928 1 1 1 2 2 2 2 2 6195.940 6175.648 0.258 1 1 2 1 1 1 1 1 6888.580 6962.940 -0.891 1 1 2 1 1 1 1 2 1181.903 1192.649 -0.311 1 1 2 1 1 1 2 1 1443.579 1456.602 -0.341 1 1 2 1 1 1 2 2 372.580 371.424 0.060 1 1 2 1 1 2 1 1 3924.055 3961.727 -0.599 1 1 2 1 1 2 1 2 1012.779 1010.214 0.081 1 1 2 1 1 2 2 1 1237.011 1233.791 0.092 1 1 2 1 1 2 2 2 472.441 468.360 0.189 1 1 2 1 2 1 1 1 13696.297 13815.722 -1.016 1 1 2 1 2 1 1 2 3534.945 3522.918 0.203 1 1 2 1 2 1 2 1 4317.592 4302.597 0.229 1 1 2 1 2 1 2 2 1648.982 1633.310 0.388 1 1 2 1 2 2 1 1 11736.431 11702.388 0.315 1 1 2 1 2 2 1 2 4482.398 4442.346 0.601 1 1 2 1 2 2 2 1 5474.813 5425.510 0.669 1 1 2 1 2 2 2 2 3076.813 3066.108 0.193 1 1 2 2 1 1 1 1 6801.380 6867.358 -0.796 1 1 2 2 1 1 1 2 1755.402 1751.131 0.102 1 1 2 2 1 1 2 1 2144.053 2138.685 0.116 1 1 2 2 1 1 2 2 818.860 811.867 0.245 1 1 2 2 1 2 1 1 5828.139 5816.886 0.148 1 1 2 2 1 2 1 2 2225.893 2208.150 0.378 1 1 2 2 1 2 2 1 2718.712 2696.849 0.421 1 1 2 2 1 2 2 2 1527.900 1524.065 0.098 1 1 2 2 2 1 1 1 20342.205 20285.214 0.400 1 1 2 2 2 1 1 2 7769.130 7700.475 0.782 1 1 2 2 2 1 2 1 9489.236 9404.716 0.872 1 1 2 2 2 1 2 2 5332.895 5314.870 0.247 1 1 2 2 2 2 1 1 25794.419 25579.349 1.345 1 1 2 2 2 2 1 2 14496.311 14455.610 0.339 1 1 2 2 2 2 2 1 17705.834 17654.873 0.384 1 1 2 2 2 2 2 2 14715.671 14853.217 -1.129 1 2 1 1 1 1 1 1 3420.768 3456.117 -0.601 1 2 1 1 1 1 1 2 586.915 591.982 -0.208 1 2 1 1 1 1 2 1 716.860 722.997 -0.228 1 2 1 1 1 1 2 2 185.018 184.359 0.049 1 2 1 1 1 2 1 1 1948.628 1966.438 -0.402 1 2 1 1 1 2 1 2 502.931 501.429 0.067 1 2 1 1 1 2 2 1 614.281 612.403 0.076 1 2 1 1 1 2 2 2 234.607 232.474 0.140 1 2 1 1 2 1 1 1 6801.380 6857.555 -0.678 1 2 1 1 2 1 1 2 1755.402 1748.631 0.162 1 2 1 1 2 1 2 1 2144.053 2135.632 0.182 1 2 1 1 2 1 2 2 818.860 810.708 0.286 1 2 1 1 2 2 1 1 5828.139 5808.583 0.257 1 2 1 1 2 2 1 2 2225.893 2204.998 0.445 1 2 1 1 2 2 2 1 2718.712 2693.000 0.495 1 2 1 1 2 2 2 2 1527.900 1521.890 0.154 1 2 1 2 1 1 1 1 3377.465 3408.673 -0.535 1 2 1 2 1 1 1 2 871.707 869.189 0.085 1 2 1 2 1 1 2 1 1064.705 1061.555 0.097 1 2 1 2 1 1 2 2 406.634 402.977 0.182 1 2 1 2 1 2 1 1 2894.168 2887.263 0.129 1 2 1 2 1 2 1 2 1105.346 1096.034 0.281 1 2 1 2 1 2 2 1 1350.072 1338.605 0.313 1 2 1 2 1 2 2 2 758.733 756.483 0.082 1 2 1 2 2 1 1 1 10101.640 10068.744 0.328 1 2 1 2 2 1 1 2 3858.036 3822.198 0.580 1 2 1 2 2 1 2 1 4712.215 4668.113 0.645 1 2 1 2 2 1 2 2 2648.237 2638.082 0.198 1 2 1 2 2 2 1 1 12809.129 12696.535 0.999 1 2 1 2 2 2 1 2 7198.655 7175.169 0.277 1 2 1 2 2 2 2 1 8792.457 8763.151 0.313 1 2 1 2 2 2 2 2 7307.586 7372.524 -0.756 1 2 2 1 1 1 1 1 1677.200 1692.351 -0.368 1 2 2 1 1 1 1 2 432.877 431.538 0.064 1 2 2 1 1 1 2 1 528.717 527.045 0.073 1 2 2 1 1 1 2 2 201.928 200.072 0.131 1 2 2 1 1 2 1 1 1437.201 1433.479 0.098 1 2 2 1 1 2 1 2 548.898 544.163 0.203 1 2 2 1 1 2 2 1 670.426 664.595 0.226 1 2 2 1 1 2 2 2 376.775 375.582 0.062 1 2 2 1 2 1 1 1 5016.326 4998.967 0.246 1 2 2 1 2 1 1 2 1915.844 1897.659 0.417 1 2 2 1 2 1 2 1 2340.017 2317.642 0.465 1 2 2 1 2 1 2 2 1315.076 1309.765 0.147 1 2 2 1 2 2 1 1 6360.825 6303.622 0.720 1 2 2 1 2 2 1 2 3574.746 3562.354 0.208 1 2 2 1 2 2 2 1 4366.205 4350.761 0.234 1 2 2 1 2 2 2 2 3628.840 3660.338 -0.521 1 2 2 2 1 1 1 1 2491.034 2484.828 0.124 1 2 2 2 1 1 1 2 951.380 943.266 0.264 1 2 2 2 1 1 2 1 1162.018 1152.026 0.294 1 2 2 2 1 1 2 2 653.047 651.043 0.079 1 2 2 2 1 2 1 1 3158.692 3133.331 0.453 1 2 2 2 1 2 1 2 1775.166 1770.733 0.105 1 2 2 2 1 2 2 1 2168.193 2162.626 0.120 1 2 2 2 1 2 2 2 1802.028 1819.438 -0.408 1 2 2 2 2 1 1 1 11024.920 10926.858 0.938 1 2 2 2 2 1 1 2 6195.940 6175.075 0.266 1 2 2 2 2 1 2 1 7567.738 7541.720 0.300 1 2 2 2 2 1 2 2 6289.697 6344.922 -0.693 1 2 2 2 2 2 1 1 20571.244 20512.292 0.412 1 2 2 2 2 2 1 2 17097.170 17257.192 -1.218 1 2 2 2 2 2 2 1 20882.531 21076.490 -1.336 1 2 2 2 2 2 2 2 26098.664 26397.526 -1.839 2 1 1 1 1 1 1 1 1698.703 1717.077 -0.443 2 1 1 1 1 1 1 2 291.454 294.110 -0.155 2 1 1 1 1 1 2 1 355.982 359.201 -0.170 2 1 1 1 1 1 2 2 91.877 91.594 0.030 2 1 1 1 1 2 1 1 967.660 976.971 -0.298 2 1 1 1 1 2 1 2 249.748 249.121 0.040 2 1 1 1 1 2 2 1 305.043 304.256 0.045 2 1 1 1 1 2 2 2 116.503 115.499 0.093 2 1 1 1 2 1 1 1 3377.465 3406.989 -0.506 2 1 1 1 2 1 1 2 871.707 868.760 0.100 2 1 1 1 2 1 2 1 1064.705 1061.030 0.113 2 1 1 1 2 1 2 2 406.634 402.778 0.192 2 1 1 1 2 2 1 1 2894.168 2885.836 0.155 2 1 1 1 2 2 1 2 1105.346 1095.493 0.298 2 1 1 1 2 2 2 1 1350.072 1337.943 0.332 2 1 1 1 2 2 2 2 758.733 756.109 0.095 2 1 1 2 1 1 1 1 1677.200 1693.506 -0.396 2 1 1 2 1 1 1 2 432.877 431.833 0.050 2 1 1 2 1 1 2 1 528.717 527.405 0.057 2 1 1 2 1 1 2 2 201.928 200.208 0.122 2 1 1 2 1 2 1 1 1437.201 1434.458 0.072 2 1 1 2 1 2 1 2 548.898 544.535 0.187 2 1 1 2 1 2 2 1 670.426 665.049 0.208 2 1 1 2 1 2 2 2 376.775 375.838 0.048 2 1 1 2 2 1 1 1 5016.326 5002.381 0.197 2 1 1 2 2 1 1 2 1915.844 1898.955 0.388 2 1 1 2 2 1 2 1 2340.017 2319.225 0.432 2 1 1 2 2 1 2 2 1315.076 1310.659 0.122 2 1 1 2 2 2 1 1 6360.825 6307.927 0.666 2 1 1 2 2 2 1 2 3574.746 3564.787 0.167 2 1 1 2 2 2 2 1 4366.205 4353.732 0.189 2 1 1 2 2 2 2 2 3628.840 3662.837 -0.562 2 1 2 1 1 1 1 1 832.873 840.798 -0.273 2 1 2 1 1 1 1 2 214.960 214.398 0.038 2 1 2 1 1 1 2 1 262.553 261.848 0.044 2 1 2 1 1 1 2 2 100.275 99.400 0.088 2 1 2 1 1 2 1 1 713.693 712.185 0.057 2 1 2 1 1 2 1 2 272.575 270.353 0.135 2 1 2 1 1 2 2 1 332.924 330.186 0.151 2 1 2 1 1 2 2 2 187.101 186.597 0.037 2 1 2 1 2 1 1 1 2491.034 2483.600 0.149 2 1 2 1 2 1 1 2 951.380 942.800 0.279 2 1 2 1 2 1 2 1 1162.018 1151.457 0.311 2 1 2 1 2 1 2 2 653.047 650.721 0.091 2 1 2 1 2 2 1 1 3158.692 3131.783 0.481 2 1 2 1 2 2 1 2 1775.166 1769.858 0.126 2 1 2 1 2 2 2 1 2168.193 2161.557 0.143 2 1 2 1 2 2 2 2 1802.028 1818.539 -0.387 2 1 2 2 1 1 1 1 1237.011 1234.519 0.071 2 1 2 2 1 1 1 2 472.441 468.636 0.176 2 1 2 2 1 1 2 1 577.041 572.353 0.196 2 1 2 2 1 1 2 2 324.294 323.453 0.047 2 1 2 2 1 2 1 1 1568.560 1556.710 0.300 2 1 2 2 1 2 1 2 881.522 879.741 0.060 2 1 2 2 1 2 2 1 1076.693 1074.442 0.069 2 1 2 2 1 2 2 2 894.861 903.938 -0.302 2 1 2 2 2 1 1 1 5474.813 5428.711 0.626 2 1 2 2 2 1 1 2 3076.813 3067.917 0.161 2 1 2 2 2 1 2 1 3758.027 3746.898 0.182 2 1 2 2 2 1 2 2 3123.371 3152.302 -0.515 2 1 2 2 2 2 1 1 10215.377 10190.972 0.242 2 1 2 2 2 2 1 2 8490.203 8573.765 -0.902 2 1 2 2 2 2 2 1 10369.958 10471.279 -0.990 2 1 2 2 2 2 2 2 12960.213 13114.890 -1.351 2 2 1 1 1 1 1 1 413.592 417.338 -0.183 2 2 1 1 1 1 1 2 106.746 106.418 0.032 2 2 1 1 1 1 2 1 130.380 129.970 0.036 2 2 1 1 1 1 2 2 49.795 49.338 0.065 2 2 1 1 1 2 1 1 354.410 353.499 0.048 2 2 1 1 1 2 1 2 135.357 134.192 0.101 2 2 1 1 1 2 2 1 165.325 163.891 0.112 2 2 1 1 1 2 2 2 92.912 92.619 0.030 2 2 1 1 2 1 1 1 1237.011 1232.757 0.121 2 2 1 1 2 1 1 2 472.441 467.967 0.207 2 2 1 1 2 1 2 1 577.041 571.536 0.230 2 2 1 1 2 1 2 2 324.294 322.991 0.072 2 2 1 1 2 2 1 1 1568.560 1554.488 0.357 2 2 1 1 2 2 1 2 881.522 878.485 0.102 2 2 1 1 2 2 2 1 1076.693 1072.908 0.116 2 2 1 1 2 2 2 2 894.861 902.648 -0.259 2 2 1 2 1 1 1 1 614.281 612.764 0.061 2 2 1 2 1 1 1 2 234.607 232.612 0.131 2 2 1 2 1 1 2 1 286.550 284.092 0.146 2 2 1 2 1 1 2 2 161.039 160.549 0.039 2 2 1 2 1 2 1 1 778.924 772.687 0.224 2 2 1 2 1 2 1 2 437.751 436.667 0.052 2 2 1 2 1 2 2 1 534.670 533.308 0.059 2 2 1 2 1 2 2 2 444.375 448.678 -0.203 2 2 1 2 2 1 1 1 2718.712 2694.588 0.465 2 2 1 2 2 1 1 2 1527.900 1522.788 0.131 2 2 1 2 2 1 2 1 1866.181 1859.806 0.148 2 2 1 2 2 1 2 2 1551.020 1564.673 -0.345 2 2 1 2 2 2 1 1 5072.806 5058.379 0.203 2 2 1 2 2 2 1 2 4216.110 4255.663 -0.606 2 2 1 2 2 2 2 1 5149.569 5197.511 -0.665 2 2 1 2 2 2 2 2 6435.851 6509.691 -0.915 2 2 2 1 1 1 1 1 305.043 304.228 0.047 2 2 2 1 1 1 1 2 116.503 115.488 0.094 2 2 2 1 1 1 2 1 142.297 141.047 0.105 2 2 2 1 1 1 2 2 79.970 79.710 0.029 2 2 2 1 1 2 1 1 386.802 383.626 0.162 2 2 2 1 1 2 1 2 217.381 216.798 0.040 2 2 2 1 1 2 2 1 265.509 264.779 0.045 2 2 2 1 1 2 2 2 220.670 222.761 -0.140 2 2 2 1 2 1 1 1 1350.072 1337.819 0.335 2 2 2 1 2 1 1 2 758.733 756.039 0.098 2 2 2 1 2 1 2 1 926.718 923.363 0.110 2 2 2 1 2 1 2 2 770.214 776.834 -0.238 2 2 2 1 2 2 1 1 2519.081 2511.402 0.153 2 2 2 1 2 2 1 2 2093.658 2112.867 -0.418 2 2 2 1 2 2 2 1 2557.200 2580.479 -0.458 2 2 2 1 2 2 2 2 3195.949 3231.955 -0.633 2 2 2 2 1 1 1 1 670.426 664.988 0.211 2 2 2 2 1 1 1 2 376.775 375.803 0.050 2 2 2 2 1 1 2 1 460.195 458.975 0.057 2 2 2 2 1 1 2 2 382.477 386.140 -0.186 2 2 2 2 1 2 1 1 1250.939 1248.339 0.074 2 2 2 2 1 2 1 2 1039.680 1050.239 -0.326 2 2 2 2 1 2 2 1 1269.868 1282.675 -0.358 2 2 2 2 1 2 2 2 1587.061 1606.503 -0.485 2 2 2 2 2 1 1 1 4366.205 4353.328 0.195 2 2 2 2 2 1 1 2 3628.840 3662.498 -0.556 2 2 2 2 2 1 2 1 4432.275 4473.068 -0.610 2 2 2 2 2 1 2 2 5539.389 5602.353 -0.841 2 2 2 2 2 2 1 1 12048.172 12166.043 -1.069 2 2 2 2 2 2 1 2 15057.619 15237.519 -1.457 2 2 2 2 2 2 2 1 18391.417 18609.831 -1.601 2 2 2 2 2 2 2 2 35638.817 34698.953 5.046 *** PSEUDO R-SQUARED MEASURES *** * P() * baseline fitted R-squared entropy 0.0000 0.0000 0.0000 qualitative variance 0.0000 0.0000 0.0000 classification error 0.0000 0.0000 0.0000 -2/N*log-likelihood 0.0000 -0.0000 0.0000/0.0000 likelihood^(-2/N) 1.0000 1.0000 0.0000/0.0000 *** LOG-LINEAR PARAMETERS *** * TABLE ABCDEFGH [or P(ABCDEFGH)] * effect beta exp(beta) main 7.4220 1.67E+0003 A 1 0.5596 1.7500 2 -0.5596 0.5714 B 1 0.2099 1.2335 2 -0.2099 0.8107 C 1 -0.1404 0.8690 2 0.1404 1.1507 D 1 -0.4905 0.6123 2 0.4905 1.6331 E 1 -0.8400 0.4317 2 0.8400 2.3163 F 1 -0.2154 0.8062 2 0.2154 1.2404 G 1 0.2849 1.3296 2 -0.2849 0.7521 H 1 0.3848 1.4694 2 -0.3848 0.6806 type 2 association (row=A column=B slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=A column=C slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=A column=D slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=A column=E slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=A column=F slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=A column=G slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=A column=H slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=B column=C slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=B column=D slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=B column=E slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=B column=F slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=B column=G slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=B column=H slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=C column=D slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=C column=E slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=C column=F slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=C column=G slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=C column=H slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=D column=E slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=D column=F slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=D column=G slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=D column=H slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=E column=F slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=E column=G slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=E column=H slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=F column=G slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=F column=H slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 type 2 association (row=G column=H slab=) association 1.0000 row -0.7071 0.7071 adj row -0.7071 0.7071 column -0.7071 0.7071 adj column -0.7071 0.7071 slab 0.1990 adj slab 0.1990 * TABLE [or P()] * effect beta exp(beta)