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 *** *data generated from rasch theta exp1 * Rasch MMLE man 8 lat 1 dim 9 2 2 2 2 2 2 2 2 lab X A B C D E F G H mod X {wei(X)} A|X {A} B|X {B} C|X {C} D|X {D} E|X {E} F|X {F} G|X {G} H|X {H} all {spe(XA,XB,XC,XD,XE,XF,XG,XH,1b)} sta wei(X) nor(1,8) nco data gen8rasch_exp1.dat *** STATISTICS *** Number of iterations = 54 Converge criterion = 0.0000006333 Seed random values = 4512 X-squared = 20558.2688 (0.0000) L-squared = 21207.6239 (0.0000) Cressie-Read = 20723.1560 (0.0000) Dissimilarity index = 0.0624 Degrees of freedom = 246 Log-likelihood = -4401662.28874 Number of parameters = 9 (+1) Sample size = 1000000.0 BIC(L-squared) = 17809.0083 AIC(L-squared) = 20715.6239 BIC(log-likelihood) = 8803448.9171 AIC(log-likelihood) = 8803342.5775 Eigenvalues information matrix 8.86E+0005 8.73E+0005 8.50E+0005 7.56E+0005 6.47E+0005 5.67E+0005 5.20E+0005 3.62E+0005 2.31E+0005 *** FREQUENCIES *** A B C D E F G H observed estimated std. res. 1 1 1 1 1 1 1 1 197.728 953.679 -24.479 1 1 1 1 1 1 1 2 118.708 255.049 -8.537 1 1 1 1 1 1 2 1 144.991 310.675 -9.400 1 1 1 1 1 1 2 2 90.495 112.128 -2.043 1 1 1 1 1 2 1 1 394.126 850.761 -15.655 1 1 1 1 1 2 1 2 245.992 307.054 -3.485 1 1 1 1 1 2 2 1 300.455 374.022 -3.804 1 1 1 1 1 2 2 2 198.304 181.755 1.228 1 1 1 1 2 1 1 1 1375.634 3045.725 -30.262 1 1 1 1 2 1 1 2 858.596 1099.254 -7.259 1 1 1 1 2 1 2 1 1048.692 1339.000 -7.934 1 1 1 1 2 1 2 2 692.149 650.684 1.626 1 1 1 1 2 2 1 1 2850.641 3666.752 -13.477 1 1 1 1 2 2 1 2 1881.457 1781.850 2.360 1 1 1 1 2 2 2 1 2298.016 2170.469 2.738 1 1 1 1 2 2 2 2 1650.617 1419.719 6.128 1 1 1 2 1 1 1 1 683.120 1491.442 -20.931 1 1 1 2 1 1 1 2 426.366 538.287 -4.824 1 1 1 2 1 1 2 1 520.765 655.687 -5.269 1 1 1 2 1 1 2 2 343.711 318.629 1.405 1 1 1 2 1 2 1 1 1415.586 1795.550 -8.967 1 1 1 2 1 2 1 2 934.304 872.543 2.091 1 1 1 2 1 2 2 1 1141.161 1062.844 2.402 1 1 1 2 1 2 2 2 819.672 695.214 4.720 1 1 1 2 2 1 1 1 4940.882 6428.067 -18.549 1 1 1 2 2 1 1 2 3261.040 3123.704 2.457 1 1 1 2 2 1 2 1 3983.044 3804.981 2.887 1 1 1 2 2 1 2 2 2860.937 2488.865 7.458 1 1 1 2 2 2 1 1 10827.036 10419.656 3.991 1 1 1 2 2 2 1 2 7776.833 6815.572 11.644 1 1 1 2 2 2 2 1 9498.646 8302.041 13.133 1 1 1 2 2 2 2 2 7813.727 7343.189 5.491 1 1 2 1 1 1 1 1 339.227 730.322 -14.472 1 1 2 1 1 1 1 2 211.727 263.586 -3.194 1 1 2 1 1 1 2 1 258.604 321.073 -3.486 1 1 2 1 1 1 2 2 170.682 156.025 1.173 1 1 2 1 1 2 1 1 702.959 879.235 -5.945 1 1 2 1 1 2 1 2 463.962 427.262 1.775 1 1 2 1 1 2 2 1 566.684 520.448 2.027 1 1 2 1 1 2 2 2 407.037 340.429 3.610 1 1 2 1 2 1 1 1 2453.569 3147.663 -12.372 1 1 2 1 2 1 1 2 1619.385 1529.599 2.296 1 1 2 1 2 1 2 1 1977.921 1863.203 2.658 1 1 2 1 2 1 2 2 1420.699 1218.735 5.785 1 1 2 1 2 2 1 1 5376.547 5102.244 3.840 1 1 2 1 2 2 1 2 3861.861 3337.414 9.078 1 1 2 1 2 2 2 1 4716.888 4065.301 10.219 1 1 2 1 2 2 2 2 3880.182 3595.775 4.743 1 1 2 2 1 1 1 1 1218.406 1541.360 -8.226 1 1 2 2 1 1 1 2 804.163 749.020 2.015 1 1 2 2 1 1 2 1 982.207 912.381 2.312 1 1 2 2 1 1 2 2 705.498 596.795 4.450 1 1 2 2 1 2 1 1 2669.914 2498.487 3.430 1 1 2 2 1 2 1 2 1917.744 1634.278 7.012 1 1 2 2 1 2 2 1 2342.337 1990.712 7.881 1 1 2 2 1 2 2 2 1926.841 1760.793 3.957 1 1 2 2 2 1 1 1 9318.916 8944.583 3.958 1 1 2 2 2 1 1 2 6693.583 5850.715 11.019 1 1 2 2 2 1 2 1 8175.560 7126.750 12.424 1 1 2 2 2 1 2 2 6725.337 6303.640 5.311 1 1 2 2 2 2 1 1 22223.477 19516.075 19.380 1 1 2 2 2 2 1 2 18281.362 17262.049 7.758 1 1 2 2 2 2 2 1 22328.906 21026.884 8.979 1 1 2 2 2 2 2 2 23118.943 25358.668 -14.065 1 2 1 1 1 1 1 1 168.455 360.629 -10.120 1 2 1 1 1 1 1 2 105.141 130.157 -2.193 1 2 1 1 1 1 2 1 128.419 158.544 -2.392 1 2 1 1 1 1 2 2 84.758 77.044 0.879 1 2 1 1 1 2 1 1 349.079 434.161 -4.083 1 2 1 1 1 2 1 2 230.396 210.980 1.337 1 2 1 1 1 2 2 1 281.407 256.994 1.523 1 2 1 1 1 2 2 2 202.129 168.102 2.624 1 2 1 1 2 1 1 1 1218.406 1554.297 -8.520 1 2 1 1 2 1 1 2 804.163 755.307 1.778 1 2 1 1 2 1 2 1 982.207 920.039 2.050 1 2 1 1 2 1 2 2 705.498 601.804 4.227 1 2 1 1 2 2 1 1 2669.914 2519.457 2.997 1 2 1 1 2 2 1 2 1917.744 1647.995 6.645 1 2 1 1 2 2 2 1 2342.337 2007.421 7.475 1 2 1 1 2 2 2 2 1926.841 1775.572 3.590 1 2 1 2 1 1 1 1 605.043 761.114 -5.657 1 2 1 2 1 1 1 2 399.335 369.862 1.533 1 2 1 2 1 1 2 1 487.749 450.528 1.754 1 2 1 2 1 1 2 2 350.340 294.694 3.242 1 2 1 2 1 2 1 1 1325.840 1233.738 2.622 1 2 1 2 1 2 1 2 952.323 806.997 5.116 1 2 1 2 1 2 2 1 1163.170 983.002 5.746 1 2 1 2 1 2 2 2 956.841 869.469 2.963 1 2 1 2 2 1 1 1 4627.637 4416.781 3.173 1 2 1 2 2 1 1 2 3323.935 2889.048 8.091 1 2 1 2 2 1 2 1 4059.863 3519.146 9.115 1 2 1 2 2 1 2 2 3339.704 3112.699 4.069 1 2 1 2 2 2 1 1 11035.852 9636.919 14.250 1 2 1 2 2 2 1 2 9078.256 8523.895 6.004 1 2 1 2 2 2 2 1 11088.206 10382.948 6.921 1 2 1 2 2 2 2 2 11480.527 12521.956 -9.307 1 2 2 1 1 1 1 1 300.455 372.698 -3.742 1 2 2 1 1 1 1 2 198.304 181.112 1.277 1 2 2 1 1 1 2 1 242.209 220.612 1.454 1 2 2 1 1 1 2 2 173.974 144.304 2.470 1 2 2 1 1 2 1 1 658.393 604.130 2.208 1 2 2 1 1 2 1 2 472.910 395.166 3.911 1 2 2 1 1 2 2 1 577.613 481.351 4.388 1 2 2 1 1 2 2 2 475.153 425.757 2.394 1 2 2 1 2 1 1 1 2298.016 2162.786 2.908 1 2 2 1 2 1 1 2 1650.617 1414.694 6.272 1 2 2 1 2 1 2 1 2016.068 1723.237 7.054 1 2 2 1 2 1 2 2 1658.448 1524.211 3.438 1 2 2 1 2 2 1 1 5480.242 4718.957 11.082 1 2 2 1 2 2 1 2 4508.128 4173.937 5.173 1 2 2 1 2 2 2 1 5506.240 5084.269 5.918 1 2 2 1 2 2 2 2 5701.061 6131.687 -5.499 1 2 2 2 1 1 1 1 1141.161 1059.082 2.522 1 2 2 2 1 1 1 2 819.672 692.753 4.822 1 2 2 2 1 1 2 1 1001.150 843.842 5.415 1 2 2 2 1 1 2 2 823.561 746.381 2.825 1 2 2 2 1 2 1 1 2721.408 2310.797 8.542 1 2 2 2 1 2 1 2 2238.670 2043.910 4.308 1 2 2 2 1 2 2 1 2734.318 2489.685 4.903 1 2 2 2 1 2 2 2 2831.063 3002.589 -3.130 1 2 2 2 2 1 1 1 9498.646 8272.655 13.479 1 2 2 2 2 1 1 2 7813.727 7317.197 5.805 1 2 2 2 2 1 2 1 9543.708 8913.071 6.680 1 2 2 2 2 1 2 2 9881.381 10749.267 -8.371 1 2 2 2 2 2 1 1 25942.487 24407.780 9.823 1 2 2 2 2 2 1 2 26860.379 29436.068 -15.013 1 2 2 2 2 2 2 1 32807.341 35856.044 -16.100 1 2 2 2 2 2 2 2 51140.991 59679.272 -34.951 2 1 1 1 1 1 1 1 83.652 181.422 -7.259 2 1 1 1 1 1 1 2 52.211 65.478 -1.640 2 1 1 1 1 1 2 1 63.771 79.759 -1.790 2 1 1 1 1 1 2 2 42.090 38.759 0.535 2 1 1 1 1 2 1 1 173.348 218.415 -3.049 2 1 1 1 1 2 1 2 114.412 106.138 0.803 2 1 1 1 1 2 2 1 139.743 129.287 0.920 2 1 1 1 1 2 2 2 100.374 84.567 1.719 2 1 1 1 2 1 1 1 605.043 781.925 -6.326 2 1 1 1 2 1 1 2 399.335 379.975 0.993 2 1 1 1 2 1 2 1 487.749 462.847 1.158 2 1 1 1 2 1 2 2 350.340 302.751 2.735 2 1 1 1 2 2 1 1 1325.840 1267.471 1.640 2 1 1 1 2 2 1 2 952.323 829.062 4.281 2 1 1 1 2 2 2 1 1163.170 1009.879 4.824 2 1 1 1 2 2 2 2 956.841 893.242 2.128 2 1 1 2 1 1 1 1 300.455 382.896 -4.213 2 1 1 2 1 1 1 2 198.304 186.067 0.897 2 1 1 2 1 1 2 1 242.209 226.649 1.034 2 1 1 2 1 1 2 2 173.974 148.252 2.112 2 1 1 2 1 2 1 1 658.393 620.660 1.515 2 1 1 2 1 2 1 2 472.910 405.978 3.322 2 1 1 2 1 2 2 1 577.613 494.522 3.736 2 1 1 2 1 2 2 2 475.153 437.406 1.805 2 1 1 2 2 1 1 1 2298.016 2221.963 1.613 2 1 1 2 2 1 1 2 1650.617 1453.402 5.173 2 1 1 2 2 1 2 1 2016.068 1770.387 5.839 2 1 1 2 2 1 2 2 1658.448 1565.915 2.338 2 1 1 2 2 2 1 1 5480.242 4848.074 9.079 2 1 1 2 2 2 1 2 4508.128 4288.141 3.359 2 1 1 2 2 2 2 1 5506.240 5223.381 3.914 2 1 1 2 2 2 2 2 5701.061 6299.458 -7.539 2 1 2 1 1 1 1 1 149.202 187.495 -2.797 2 1 2 1 1 1 1 2 98.475 91.113 0.771 2 1 2 1 1 1 2 1 120.278 110.984 0.882 2 1 2 1 1 1 2 2 86.393 72.595 1.619 2 1 2 1 1 2 1 1 326.948 303.922 1.321 2 1 2 1 1 2 1 2 234.840 198.797 2.556 2 1 2 1 1 2 2 1 286.834 242.155 2.871 2 1 2 1 1 2 2 2 235.954 214.187 1.487 2 1 2 1 2 1 1 1 1141.161 1088.039 1.610 2 1 2 1 2 1 1 2 819.672 711.694 4.048 2 1 2 1 2 1 2 1 1001.150 866.914 4.559 2 1 2 1 2 1 2 2 823.561 766.789 2.050 2 1 2 1 2 2 1 1 2721.408 2373.980 7.131 2 1 2 1 2 2 1 2 2238.670 2099.795 3.031 2 1 2 1 2 2 2 1 2734.318 2557.758 3.491 2 1 2 1 2 2 2 2 2831.063 3084.686 -4.567 2 1 2 2 1 1 1 1 566.684 532.795 1.468 2 1 2 2 1 1 1 2 407.037 348.505 3.135 2 1 2 2 1 1 2 1 497.156 424.514 3.526 2 1 2 2 1 1 2 2 408.968 375.484 1.728 2 1 2 2 1 2 1 1 1351.411 1162.500 5.541 2 1 2 2 1 2 1 2 1111.691 1028.236 2.603 2 1 2 2 1 2 2 1 1357.822 1252.493 2.976 2 1 2 2 1 2 2 2 1405.864 1510.521 -2.693 2 1 2 2 2 1 1 1 4716.888 4161.749 8.605 2 1 2 2 2 1 1 2 3880.182 3681.084 3.282 2 1 2 2 2 1 2 1 4739.265 4483.925 3.813 2 1 2 2 2 1 2 2 4906.949 5407.666 -6.809 2 1 2 2 2 2 1 1 12882.658 12278.895 5.449 2 1 2 2 2 2 1 2 13338.470 14808.491 -12.080 2 1 2 2 2 2 2 1 16291.643 18038.208 -13.004 2 1 2 2 2 2 2 2 25395.864 30023.031 -26.705 2 2 1 1 1 1 1 1 74.091 92.584 -1.922 2 2 1 1 1 1 1 2 48.901 44.991 0.583 2 2 1 1 1 1 2 1 59.728 54.803 0.665 2 2 1 1 1 1 2 2 42.901 35.847 1.178 2 2 1 1 1 2 1 1 162.358 150.075 1.003 2 2 1 1 1 2 1 2 116.618 98.165 1.862 2 2 1 1 1 2 2 1 142.438 119.575 2.091 2 2 1 1 1 2 2 2 117.171 105.764 1.109 2 2 1 1 2 1 1 1 566.684 537.267 1.269 2 2 1 1 2 1 1 2 407.037 351.430 2.966 2 2 1 1 2 1 2 1 497.156 428.077 3.339 2 2 1 1 2 1 2 2 408.968 378.636 1.559 2 2 1 1 2 2 1 1 1351.411 1172.257 5.233 2 2 1 1 2 2 1 2 1111.691 1036.866 2.324 2 2 1 1 2 2 2 1 1357.822 1263.006 2.668 2 2 1 1 2 2 2 2 1405.864 1523.199 -3.006 2 2 1 2 1 1 1 1 281.407 263.091 1.129 2 2 1 2 1 1 1 2 202.129 172.090 2.290 2 2 1 2 1 1 2 1 246.881 209.622 2.573 2 2 1 2 1 1 2 2 203.088 185.412 1.298 2 2 1 2 1 2 1 1 671.091 574.035 4.051 2 2 1 2 1 2 1 2 552.049 507.737 1.967 2 2 1 2 1 2 2 1 674.275 618.473 2.244 2 2 1 2 1 2 2 2 698.132 745.886 -1.749 2 2 1 2 2 1 1 1 2342.337 2055.047 6.337 2 2 1 2 2 1 1 2 1926.841 1817.697 2.560 2 2 1 2 2 1 2 1 2353.449 2214.135 2.961 2 2 1 2 2 1 2 2 2436.719 2670.273 -4.520 2 2 1 2 2 2 1 1 6397.339 6063.244 4.291 2 2 1 2 2 2 1 2 6623.688 7312.343 -8.053 2 2 1 2 2 2 2 1 8090.191 8907.158 -8.656 2 2 1 2 2 2 2 2 12611.213 14825.190 -18.183 2 2 2 1 1 1 1 1 139.743 128.829 0.962 2 2 2 1 1 1 1 2 100.374 84.268 1.755 2 2 2 1 1 1 2 1 122.597 102.647 1.969 2 2 2 1 1 1 2 2 100.850 90.792 1.056 2 2 2 1 1 2 1 1 333.254 281.091 3.111 2 2 2 1 1 2 1 2 274.140 248.626 1.618 2 2 2 1 1 2 2 1 334.835 302.851 1.838 2 2 2 1 1 2 2 2 346.682 365.242 -0.971 2 2 2 1 2 1 1 1 1163.170 1006.305 4.945 2 2 2 1 2 1 1 2 956.841 890.081 2.238 2 2 2 1 2 1 2 1 1168.688 1084.206 2.566 2 2 2 1 2 1 2 2 1210.039 1307.565 -2.697 2 2 2 1 2 2 1 1 3176.824 2969.018 3.814 2 2 2 1 2 2 1 2 3289.226 3580.671 -4.871 2 2 2 1 2 2 2 1 4017.470 4361.611 -5.211 2 2 2 1 2 2 2 2 6262.543 7259.523 -11.701 2 2 2 2 1 1 1 1 577.613 492.771 3.822 2 2 2 2 1 1 1 2 475.153 435.858 1.882 2 2 2 2 1 1 2 1 580.353 530.918 2.145 2 2 2 2 1 1 2 2 600.887 640.294 -1.557 2 2 2 2 1 2 1 1 1577.564 1453.880 3.244 2 2 2 2 1 2 1 2 1633.381 1753.397 -2.866 2 2 2 2 1 2 2 1 1995.016 2135.811 -3.047 2 2 2 2 1 2 2 2 3109.887 3554.872 -7.463 2 2 2 2 2 1 1 1 5506.240 5204.892 4.177 2 2 2 2 2 1 1 2 5701.061 6277.160 -7.271 2 2 2 2 2 1 2 1 6963.292 7646.203 -7.810 2 2 2 2 2 1 2 2 10854.572 12726.441 -16.593 2 2 2 2 2 2 1 1 18928.189 20938.557 -13.893 2 2 2 2 2 2 1 2 29505.785 34850.410 -28.629 2 2 2 2 2 2 2 1 36038.447 42451.249 -31.125 2 2 2 2 2 2 2 2 123173.480 99239.898 75.974 *** PSEUDO R-SQUARED MEASURES *** * P(A|X) * baseline fitted R-squared entropy 0.6916 0.6323 0.0858 qualitative variance 0.2492 0.2211 0.1129 classification error 0.4724 0.3622 0.2333 -2/N*log-likelihood 1.3833 1.2547 0.0929/0.1139 likelihood^(-2/N) 3.9879 3.5069 0.1206/0.1610 * P(B|X) * baseline fitted R-squared entropy 0.6628 0.6069 0.0844 qualitative variance 0.2350 0.2098 0.1074 classification error 0.3775 0.3285 0.1297 -2/N*log-likelihood 1.3256 1.2121 0.0857/0.1020 likelihood^(-2/N) 3.7646 3.3605 0.1074/0.1462 * P(C|X) * baseline fitted R-squared entropy 0.5546 0.5099 0.0806 qualitative variance 0.1840 0.1675 0.0895 classification error 0.2431 0.2353 0.0320 -2/N*log-likelihood 1.1092 1.0240 0.0768/0.0785 likelihood^(-2/N) 3.0321 2.7844 0.0817/0.1219 * P(D|X) * baseline fitted R-squared entropy 0.4095 0.3789 0.0748 qualitative variance 0.1222 0.1142 0.0653 classification error 0.1425 0.1420 0.0035 -2/N*log-likelihood 0.8191 0.7640 0.0673/0.0522 likelihood^(-2/N) 2.2684 2.1468 0.0536/0.0959 * P(E|X) * baseline fitted R-squared entropy 0.2738 0.2552 0.0678 qualitative variance 0.0719 0.0689 0.0423 classification error 0.0780 0.0780 0.0001 -2/N*log-likelihood 0.5476 0.5157 0.0582/0.0309 likelihood^(-2/N) 1.7291 1.6748 0.0314/0.0744 * P(F|X) * baseline fitted R-squared entropy 0.5248 0.4831 0.0795 qualitative variance 0.1707 0.1562 0.0846 classification error 0.2184 0.2148 0.0165 -2/N*log-likelihood 1.0497 0.9712 0.0748/0.0728 likelihood^(-2/N) 2.8568 2.6410 0.0755/0.1162 * P(G|X) * baseline fitted R-squared entropy 0.6766 0.6191 0.0849 qualitative variance 0.2418 0.2152 0.1097 classification error 0.4092 0.3387 0.1722 -2/N*log-likelihood 1.3531 1.2349 0.0874/0.1057 likelihood^(-2/N) 3.8695 3.4380 0.1115/0.1504 * P(H|X) * baseline fitted R-squared entropy 0.6886 0.6297 0.0854 qualitative variance 0.2477 0.2200 0.1119 classification error 0.4522 0.3544 0.2163 -2/N*log-likelihood 1.3771 1.2539 0.0895/0.1098 likelihood^(-2/N) 3.9635 3.5038 0.1160/0.1551 *** LOG-LINEAR PARAMETERS *** * TABLE XA [or P(A|X)] * effect beta std err z-value exp(beta) Wald df prob A 1 0.0613 0.0011 54.321 1.0632 2 -0.0613 0.9405 2950.77 1 0.000 * TABLE XB [or P(B|X)] * effect beta std err z-value exp(beta) Wald df prob B 1 -0.2822 0.0012 -243.194 0.7541 2 0.2822 1.3260 59143.10 1 0.000 * TABLE XC [or P(C|X)] * effect beta std err z-value exp(beta) Wald df prob C 1 -0.6350 0.0013 -489.425 0.5299 2 0.6350 1.8871 239537.14 1 0.000 * TABLE XD [or P(D|X)] * effect beta std err z-value exp(beta) Wald df prob D 1 -0.9920 0.0016 -636.629 0.3708 2 0.9920 2.6967 405296.45 1 0.000 * TABLE XE [or P(E|X)] * effect beta std err z-value exp(beta) Wald df prob E 1 -1.3490 0.0020 -681.662 0.2595 2 1.3490 3.8537 464662.90 1 0.000 * TABLE XF [or P(F|X)] * effect beta std err z-value exp(beta) Wald df prob F 1 -0.7113 0.0013 -530.043 0.4910 2 0.7113 2.0367 280945.08 1 0.000 * TABLE XG [or P(G|X)] * effect beta std err z-value exp(beta) Wald df prob G 1 -0.2077 0.0011 -181.332 0.8125 2 0.2077 1.2308 32881.30 1 0.000 * TABLE XH [or P(H|X)] * effect beta std err z-value exp(beta) Wald df prob H 1 -0.1090 0.0011 -96.287 0.8967 2 0.1090 1.1152 9271.10 1 0.000 * ALL TABLES * effect beta std err z-value exp(beta) Wald df prob spe(XA,.,XH,1b) 1 0.7538 0.0014 524.524 2.1250 275125.75 1 0.000 *** LATENT CLASS OUTPUT *** X 1 X 2 X 3 X 4 X 5 X 6 X 7 X 8 0.0001 0.0044 0.0540 0.2420 0.3989 0.2420 0.0540 0.0044 A 1 0.9584 0.9156 0.8362 0.7061 0.5306 0.3473 0.2002 0.1054 A 2 0.0416 0.0844 0.1638 0.2939 0.4694 0.6527 0.7998 0.8946 B 1 0.9206 0.8451 0.7197 0.5472 0.3625 0.2111 0.1119 0.0560 B 2 0.0794 0.1549 0.2803 0.4528 0.6375 0.7889 0.8881 0.9440 C 1 0.8513 0.7293 0.5591 0.3737 0.2193 0.1167 0.0585 0.0284 C 2 0.1487 0.2707 0.4409 0.6263 0.7807 0.8833 0.9415 0.9716 D 1 0.7371 0.5689 0.3831 0.2261 0.1209 0.0608 0.0296 0.0141 D 2 0.2629 0.4311 0.6169 0.7739 0.8791 0.9392 0.9704 0.9859 E 1 0.5786 0.3925 0.2332 0.1252 0.0631 0.0307 0.0147 0.0070 E 2 0.4214 0.6075 0.7668 0.8748 0.9369 0.9693 0.9853 0.9930 F 1 0.8309 0.6982 0.5212 0.3387 0.1942 0.1019 0.0507 0.0245 F 2 0.1691 0.3018 0.4788 0.6613 0.8058 0.8981 0.9493 0.9755 G 1 0.9308 0.8637 0.7488 0.5838 0.3976 0.2370 0.1275 0.0644 G 2 0.0692 0.1363 0.2512 0.4162 0.6024 0.7630 0.8725 0.9356 H 1 0.9425 0.8853 0.7841 0.6308 0.4457 0.2745 0.1512 0.0773 H 2 0.0575 0.1147 0.2159 0.3692 0.5543 0.7255 0.8488 0.9227 X 9 0.0001 A 1 0.0525 A 2 0.9475 B 1 0.0271 B 2 0.9729 C 1 0.0136 C 2 0.9864 D 1 0.0067 D 2 0.9933 E 1 0.0033 E 2 0.9967 F 1 0.0117 F 2 0.9883 G 1 0.0314 G 2 0.9686 H 1 0.0379 H 2 0.9621 E = 0.5018, lambda = 0.1651