---------------------------------------------------------------------------------- log: C:\AAA Miker Files\newer web pages\soc_388_notes\soc_388_2002\class 9 > _2002.log log type: text opened on: 30 Oct 2002, 13:50:22 . use "C:\AAA Miker Files\newer web pages\soc_388_notes\soc_388_2002\HW3 dataset w > ith best fit vars.dta", clear . *This is the dataset from HW3 . table meth feth , by(mgen fgen year) contents (sum count) row col ---------------------------------------------------------- mgen, | fgen, | year and | feth meth | Blk_NH Mex_Am Oth_H Oth_NH Wht_NH Total ----------+----------------------------------------------- foreign | foreign | 70 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------- foreign | foreign | 80 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------- foreign | foreign | 90 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------- foreign | US native | 70 | Blk_NH | 25 0 3 0 3 31 Mex_Am | 0 85 8 2 33 128 Oth_H | 6 3 35 0 64 108 Oth_NH | 0 5 1 14 20 40 Wht_NH | 3 8 12 5 773 801 | Total | 34 101 59 21 893 1108 ----------+----------------------------------------------- foreign | US native | 80 | Blk_NH | 381 5 3 2 50 441 Mex_Am | 5 1586 68 41 413 2113 Oth_H | 66 147 628 21 789 1651 Oth_NH | 21 33 10 132 405 601 Wht_NH | 11 105 50 56 5020 5242 | Total | 484 1876 759 252 6677 10048 ----------+----------------------------------------------- foreign | US native | 90 | Blk_NH | 315 7 11 5 54 392 Mex_Am | 14 1653 85 43 482 2277 Oth_H | 46 131 627 19 640 1463 Oth_NH | 14 42 20 123 391 590 Wht_NH | 20 88 47 40 3752 3947 | Total | 409 1921 790 230 5319 8669 ----------+----------------------------------------------- US native | foreign | 70 | Blk_NH | 12 1 6 5 6 30 Mex_Am | 0 76 3 3 9 91 Oth_H | 1 7 12 3 14 37 Oth_NH | 1 1 1 15 2 20 Wht_NH | 0 35 71 94 1083 1283 | Total | 14 120 93 120 1114 1461 ----------+----------------------------------------------- US native | foreign | 80 | Blk_NH | 329 12 68 138 96 643 Mex_Am | 2 919 78 45 78 1122 Oth_H | 5 22 401 26 61 515 Oth_NH | 2 13 12 148 40 215 Wht_NH | 12 239 686 1176 5151 7264 | Total | 350 1205 1245 1533 5426 9759 ----------+----------------------------------------------- US native | foreign | 90 | Blk_NH | 230 26 60 79 65 460 Mex_Am | 1 878 66 43 60 1048 Oth_H | 12 36 481 35 38 602 Oth_NH | 2 17 20 158 34 231 Wht_NH | 36 296 632 1012 3629 5605 | Total | 281 1253 1259 1327 3826 7946 ----------+----------------------------------------------- US native | US native | 70 | Blk_NH | 4596 5 23 7 67 4698 Mex_Am | 0 756 27 5 232 1020 Oth_H | 16 26 1006 6 246 1300 Oth_NH | 2 7 7 257 130 403 Wht_NH | 38 186 224 134 54331 54913 | Total | 4652 980 1287 409 55006 62334 ----------+----------------------------------------------- US native | US native | 80 | Blk_NH | 24628 126 129 91 914 25888 Mex_Am | 29 7116 156 144 2556 10001 Oth_H | 80 139 1514 68 1492 3293 Oth_NH | 33 95 81 1527 1545 3281 Wht_NH | 232 2171 1454 1558 280562 285977 | Total | 25002 9647 3334 3388 287069 328440 ----------+----------------------------------------------- US native | US native | 90 | Blk_NH | 12005 109 109 66 809 13098 Mex_Am | 43 5019 121 107 2204 7494 Oth_H | 78 122 1197 80 1163 2640 Oth_NH | 26 104 62 1135 1392 2719 Wht_NH | 263 2210 1227 1430 188975 194105 | Total | 12415 7564 2716 2818 194543 220056 ---------------------------------------------------------- . describe Contains data from C:\AAA Miker Files\newer web pages\soc_388_notes\soc_388_2002 > \HW3 dataset with best fit vars.dta obs: 225 vars: 169 24 Oct 2002 11:00 size: 42,525 (98.8% of memory free) ------------------------------------------------------------------------------- storage display value variable name type format label variable label ------------------------------------------------------------------------------- meth str6 %9s feth str6 %9s mgen byte %9.0g gen fgen byte %9.0g gen year byte %8.0g count long %12.0g Frequency ethintdm byte %9.0g ethintct byte %9.0g BW byte %9.0g MOh byte %9.0g QS byte %9.0g QS PrettyGood float %9.0g predicted number of events BOhS byte %9.0g BWS byte %9.0g _x_1 byte %8.0g year==80 _x_2 byte %8.0g year==90 _x_3 byte %8.0g __0014ST==2 _x_4 byte %8.0g __0014ST==3 _x_5 byte %8.0g __0014ST==4 _x_6 byte %8.0g __0014ST==5 _x_7 byte %9.0g year==80.__0014ST==2 _x_8 byte %9.0g year==80.__0014ST==3 _x_9 byte %9.0g year==80.__0014ST==4 _x_10 byte %9.0g year==90.__0014ST==2 _x_11 byte %9.0g year==90.__0014ST==3 _x_12 byte %9.0g year==90.__0014ST==4 _x_13 byte %9.0g year==90.__0014ST==5 _x_14 byte %8.0g mgen==2 _x_15 byte %9.0g __0014ST==2.mgen==2 _x_16 byte %9.0g __0014ST==3.mgen==2 _x_17 byte %9.0g __0014ST==4.mgen==2 _x_18 byte %9.0g __0014ST==5.mgen==2 _x_19 byte %9.0g year==80.__0014ST==3.mgen==2 _x_20 byte %9.0g year==80.__0014ST==4.mgen==2 _x_21 byte %9.0g year==80.__0014ST==5.mgen==2 _x_22 byte %9.0g year==90.__0014ST==2.mgen==2 _x_23 byte %9.0g year==90.__0014ST==3.mgen==2 _x_24 byte %9.0g year==90.__0014ST==4.mgen==2 _x_25 byte %9.0g year==90.__0014ST==5.mgen==2 _x_26 byte %8.0g fgen==2 _x_27 byte %9.0g __0014ST==2.fgen==2 _x_28 byte %9.0g __0014ST==3.fgen==2 _x_29 byte %9.0g __0014ST==5.fgen==2 _x_30 byte %9.0g year==80.__0014ST==2.fgen==2 _x_31 byte %9.0g year==80.__0014ST==5.fgen==2 _x_32 byte %9.0g year==90.__0014ST==3.fgen==2 _x_33 byte %9.0g year==90.__0014ST==4.fgen==2 _x_34 byte %9.0g year==80.mgen==2.fgen==2 _x_35 byte %9.0g year==90.mgen==2.fgen==2 _x_36 byte %9.0g __0014ST==4.mgen==2.fgen==2 _x_37 byte %9.0g year==80.__0014ST==2.mgen==2.fg en==2 _x_38 byte %9.0g year==80.__0014ST==3.mgen==2.fg en==2 _x_39 byte %9.0g year==80.__0014ST==4.mgen==2.fg en==2 _x_40 byte %9.0g year==80.__0014ST==5.mgen==2.fg en==2 _x_41 byte %9.0g year==90.__0014ST==2.mgen==2.fg en==2 _x_42 byte %9.0g year==90.__0014ST==5.mgen==2.fg en==2 _x_43 byte %8.0g __0014SY==2 _x_44 byte %8.0g __0014SY==3 _x_45 byte %8.0g __0014SY==4 _x_46 byte %8.0g __0014SY==5 _x_47 byte %9.0g year==80.__0014SY==2 _x_48 byte %9.0g year==80.__0014SY==3 _x_49 byte %9.0g year==80.__0014SY==4 _x_50 byte %9.0g year==80.__0014SY==5 _x_51 byte %9.0g year==90.__0014SY==2 _x_52 byte %9.0g year==90.__0014SY==3 _x_53 byte %9.0g year==90.__0014SY==4 _x_54 byte %9.0g year==90.__0014SY==5 _x_55 byte %9.0g year==80.fgen==2 _x_56 byte %9.0g year==90.fgen==2 _x_57 byte %9.0g __0014SY==2.fgen==2 _x_58 byte %9.0g __0014SY==3.fgen==2 _x_59 byte %9.0g __0014SY==4.fgen==2 _x_60 byte %9.0g __0014SY==5.fgen==2 _x_61 byte %9.0g year==80.__0014SY==3.fgen==2 _x_62 byte %9.0g year==80.__0014SY==4.fgen==2 _x_63 byte %9.0g year==80.__0014SY==5.fgen==2 _x_64 byte %9.0g year==90.__0014SY==2.fgen==2 _x_65 byte %9.0g year==90.__0014SY==3.fgen==2 _x_66 byte %9.0g year==90.__0014SY==4.fgen==2 _x_67 byte %9.0g year==90.__0014SY==5.fgen==2 _x_68 byte %9.0g __0014SY==2.mgen==2 _x_69 byte %9.0g __0014SY==3.mgen==2 _x_70 byte %9.0g __0014SY==5.mgen==2 _x_71 byte %9.0g year==80.__0014SY==2.mgen==2 _x_72 byte %9.0g year==80.__0014SY==3.mgen==2 _x_73 byte %9.0g year==80.__0014SY==4.mgen==2 _x_74 byte %9.0g year==90.__0014SY==2.mgen==2 _x_75 byte %9.0g year==90.__0014SY==3.mgen==2 _x_76 byte %9.0g year==90.__0014SY==4.mgen==2 _x_77 byte %9.0g __0014SY==4.fgen==2.mgen==2 _x_78 byte %9.0g year==80.__0014SY==2.fgen==2.mg en==2 _x_79 byte %9.0g year==80.__0014SY==5.fgen==2.mg en==2 _x_80 byte %9.0g year==90.__0014SY==5.fgen==2.mg en==2 _x_81 byte %8.0g ethintct==1 _x_82 byte %8.0g ethintct==2 _x_83 byte %8.0g ethintct==3 _x_84 byte %8.0g ethintct==5 _x_85 byte %9.0g ethintct==1.year==80 _x_86 byte %9.0g ethintct==1.year==90 _x_87 byte %9.0g ethintct==2.year==90 _x_88 byte %9.0g ethintct==3.year==80 _x_89 byte %9.0g ethintct==3.year==90 _x_90 byte %9.0g ethintct==4.year==80 _x_91 byte %9.0g ethintct==4.year==90 _x_92 byte %9.0g ethintct==5.year==80 _x_93 byte %9.0g ethintct==5.year==90 _x_94 byte %9.0g ethintct==1.fgen==2 _x_95 byte %9.0g ethintct==2.fgen==2 _x_96 byte %9.0g ethintct==3.fgen==2 _x_97 byte %9.0g ethintct==4.fgen==2 _x_98 byte %9.0g ethintct==5.fgen==2 _x_99 byte %9.0g ethintct==1.year==80.fgen==2 _x_100 byte %9.0g ethintct==1.year==90.fgen==2 _x_101 byte %9.0g ethintct==2.year==80.fgen==2 _x_102 byte %9.0g ethintct==2.year==90.fgen==2 _x_103 byte %9.0g ethintct==3.year==90.fgen==2 _x_104 byte %9.0g ethintct==4.year==80.fgen==2 _x_105 byte %9.0g ethintct==4.year==90.fgen==2 _x_106 byte %9.0g ethintct==5.year==90.fgen==2 _x_107 byte %9.0g ethintct==2.mgen==2 _x_108 byte %9.0g ethintct==3.mgen==2 _x_109 byte %9.0g ethintct==4.mgen==2 _x_110 byte %9.0g ethintct==1.year==80.mgen==2 _x_111 byte %9.0g ethintct==2.year==80.mgen==2 _x_112 byte %9.0g ethintct==3.year==80.mgen==2 _x_113 byte %9.0g ethintct==3.year==90.mgen==2 _x_114 byte %9.0g ethintct==5.year==80.mgen==2 _x_115 byte %9.0g ethintct==5.year==90.mgen==2 _x_116 byte %9.0g ethintct==1.fgen==2.mgen==2 _x_117 byte %9.0g ethintct==4.fgen==2.mgen==2 _x_118 byte %9.0g ethintct==5.fgen==2.mgen==2 _x_119 byte %9.0g ethintct==1.year==90.fgen==2.mg en==2 _x_120 byte %9.0g ethintct==2.year==80.fgen==2.mg en==2 _x_121 byte %9.0g ethintct==2.year==90.fgen==2.mg en==2 _x_122 byte %9.0g ethintct==3.year==80.fgen==2.mg en==2 _x_123 byte %9.0g ethintct==4.year==80.fgen==2.mg en==2 _x_124 byte %9.0g ethintct==4.year==90.fgen==2.mg en==2 _x_125 byte %9.0g ethintct==5.year==80.fgen==2.mg en==2 _x_126 byte %8.0g QS==1 _x_127 byte %8.0g QS==2 _x_128 byte %8.0g QS==3 _x_129 byte %8.0g QS==4 _x_130 byte %8.0g QS==5 _x_131 byte %8.0g BOhS==1 _x_132 byte %8.0g BWS==1 _x_133 byte %9.0g QS==1.year==80 _x_134 byte %9.0g QS==1.year==90 _x_135 byte %9.0g QS==2.year==80 _x_136 byte %9.0g QS==2.year==90 _x_137 byte %9.0g QS==3.year==80 _x_138 byte %9.0g QS==3.year==90 _x_139 byte %9.0g QS==4.year==80 _x_140 byte %9.0g QS==4.year==90 _x_141 byte %9.0g QS==5.year==80 _x_142 byte %9.0g QS==5.year==90 _x_143 byte %9.0g QS==1.mgen==2 _x_144 byte %9.0g QS==2.mgen==2 _x_145 byte %9.0g QS==3.mgen==2 _x_146 byte %9.0g QS==4.mgen==2 _x_147 byte %9.0g QS==5.mgen==2 _x_148 byte %9.0g QS==1.fgen==2 _x_149 byte %9.0g QS==2.fgen==2 _x_150 byte %9.0g QS==3.fgen==2 _x_151 byte %9.0g QS==4.fgen==2 _x_152 byte %9.0g QS==5.fgen==2 _x_153 byte %9.0g BOhS==1.fgen==2 _x_154 byte %9.0g BWS==1.year==80 _x_155 byte %9.0g BWS==1.year==90 ------------------------------------------------------------------------------- Sorted by: . *it is my claim that the meth*mgen*fgen*year and feth*mgen*fgen*year model wil > l fit the marginals of each of these 9 tables. . desmat: poisson count meth*mgen*fgen*year feth*mgen*fgen*year ------------------------------------------------------------------------------- poisson ------------------------------------------------------------------------------- Dependent variable count Number of observations: 225 Initial log likelihood: -2252613.647 Log likelihood: -218651.163 LR chi square: 4067924.968 Model degrees of freedom: 80 Pseudo R-squared: 0.903 Prob: 0.000 ------------------------------------------------------------------------------- nr Effect Coeff s.e. ------------------------------------------------------------------------------- count meth 1 Mex_Am 4.055** 0.293 2 Oth_H 2.743** 0.321 3 Oth_NH 0.255 0.239 4 Wht_NH 4.549** 0.260 mgen 5 US native 5.910** 0.247 meth.mgen 6 Mex_Am.US native -2.945** 0.203 7 Oth_H.US native -2.533** 0.206 8 Oth_NH.US native -0.660 0.375 9 Wht_NH.US native -0.793** 0.184 fgen 10 US native 7.106** 0.323 meth.fgen 11 Mex_Am.US native -2.637** 0.213 12 Oth_H.US native -1.495** 0.248 13 Wht_NH.US native -1.297** 0.185 meth.mgen.fgen 14 Oth_NH.US native.US native -2.050** 0.293 year 15 80 4.385** 0.329 16 90 2.967** 0.256 meth.year 17 Mex_Am.80 0.149 0.207 18 Mex_Am.90 -0.286 0.218 19 Oth_H.80 0.072 0.211 20 Oth_H.90 0.445 0.332 21 Oth_NH.80 0.055 0.247 22 Oth_NH.90 -1.013** 0.393 23 Wht_NH.90 -1.256** 0.191 mgen.year 24 US native.90 1.068* 0.419 meth.mgen.year 25 Mex_Am.US native.80 -0.702* 0.299 26 Oth_H.US native.80 -0.504 0.329 27 Oth_H.US native.90 -0.386 0.215 28 Oth_NH.US native.80 -0.745 0.388 29 Oth_NH.US native.90 0.730** 0.254 30 Wht_NH.US native.80 -1.331** 0.189 fgen.year 31 US native.80 -1.279** 0.416 meth.fgen.year 32 Mex_Am.US native.90 0.628* 0.301 33 Oth_H.US native.90 -0.376 0.256 34 Oth_NH.US native.90 1.167** 0.305 35 Wht_NH.US native.80 -0.776** 0.190 36 Wht_NH.US native.90 0.313 0.270 mgen.fgen.year 37 US native.US native.80 -1.380** 0.256 38 US native.US native.90 -3.290** 0.332 meth.mgen.fgen.year 39 Mex_Am.US native.US native.80 1.129** 0.219 40 Mex_Am.US native.US native.90 0.628** 0.211 41 Oth_H.US native.US native.80 -0.345 0.255 42 Oth_NH.US native.US native.80 1.080** 0.304 43 Wht_NH.US native.US native.80 2.051** 0.268 44 Wht_NH.US native.US native.90 1.180** 0.191 feth 45 Mex_Am 4.795** 0.347 46 Oth_H 3.730** 0.360 47 Oth_NH -0.482 0.278 48 Wht_NH 5.175** 0.321 feth.mgen 49 Mex_Am.US native -2.646** 0.201 50 Oth_H.US native -1.836** 0.218 51 Oth_NH.US native 2.630** 0.396 52 Wht_NH.US native -0.798** 0.175 feth.fgen 53 Mex_Am.US native -3.706** 0.285 54 Oth_H.US native -3.179** 0.288 55 Wht_NH.US native -1.907** 0.269 feth.mgen.fgen 56 Oth_NH.US native.US native -4.580** 0.287 feth.year 57 Mex_Am.80 -0.912** 0.289 58 Mex_Am.90 -1.257** 0.358 59 Oth_H.80 0.004 0.370 60 Oth_H.90 -0.394 0.294 61 Oth_NH.80 -1.275** 0.411 62 Oth_NH.90 -1.638** 0.414 63 Wht_NH.80 -1.636** 0.275 64 Wht_NH.90 -0.703** 0.182 feth.mgen.year 65 Mex_Am.US native.90 0.604** 0.209 66 Oth_H.US native.80 -0.629** 0.226 67 Oth_NH.US native.80 0.603* 0.293 68 Oth_NH.US native.90 1.042** 0.295 69 Wht_NH.US native.90 -1.063** 0.331 feth.fgen.year 70 Mex_Am.US native.80 1.178** 0.354 71 Mex_Am.US native.90 1.715** 0.293 72 Oth_H.US native.80 -0.105 0.295 73 Oth_H.US native.90 0.501 0.370 74 Oth_NH.US native.80 1.104** 0.294 75 Oth_NH.US native.90 1.545** 0.295 76 Wht_NH.US native.80 0.992** 0.329 feth.mgen.fgen.year 77 Mex_Am.US native.US native.80 0.339 0.208 78 Oth_H.US native.US native.90 -0.342 0.227 79 Wht_NH.US native.US native.80 0.615** 0.182 80 Wht_NH.US native.US native.90 2.047** 0.277 81 _cons -7.156** 0.407 ------------------------------------------------------------------------------- * p < .05 ** p < .01 . poisgof Goodness-of-fit chi2 = 435970.3 Prob > chi2(144) = 0.0000 . predict marginalsby9 (option n assumed; predicted number of events) . table meth feth , by(mgen fgen year) contents (sum marginalsby9) row col ---------------------------------------------------------------------- mgen, | fgen, | year and | feth meth | Blk_NH Mex_Am Oth_H Oth_NH Wht_NH Total ----------+----------------------------------------------------------- foreign | foreign | 70 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------------------- foreign | foreign | 80 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------------------- foreign | foreign | 90 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------------------- foreign | US native | 70 | Blk_NH | .9512635 2.825812 1.650722 .5875451 24.98466 31 Mex_Am | 3.927798 11.66787 6.815885 2.425993 103.1625 128 Oth_H | 3.31408 9.844766 5.750903 2.046932 87.04332 108 Oth_NH | 1.227437 3.646209 2.129964 .7581227 32.23827 40 Wht_NH | 24.57942 73.01534 42.65253 15.18141 645.5713 801 | Total | 34 101 59 21 893 1108 ----------+----------------------------------------------------------- foreign | US native | 80 | Blk_NH | 21.24244 82.33639 33.312 11.06011 293.0491 441 Mex_Am | 101.7807 394.5052 159.6106 52.99323 1404.11 2113 Oth_H | 79.52667 308.248 124.7123 41.40645 1097.107 1651 Oth_NH | 28.94944 112.209 45.39799 15.07285 399.3707 601 Wht_NH | 252.5008 978.7014 395.9672 131.4674 3483.363 5242 | Total | 484 1876 759 252 6677 10048 ----------+----------------------------------------------------------- foreign | US native | 90 | Blk_NH | 18.49441 86.86492 35.72269 10.40028 240.5177 392 Mex_Am | 107.428 504.5699 207.5014 60.41181 1397.089 2277 Oth_H | 69.02377 324.1923 133.3222 38.81532 897.6464 1463 Oth_NH | 27.83597 130.7406 53.76629 15.65348 362.0037 590 Wht_NH | 186.2179 874.6323 359.6874 104.7191 2421.743 3947 | Total | 409 1921 790 230 5319 8669 ----------+----------------------------------------------------------- US native | foreign | 70 | Blk_NH | .2874743 2.464066 1.909651 2.464066 22.87474 30 Mex_Am | .8720055 7.474333 5.792608 7.474333 69.38672 91 Oth_H | .354625 3.039643 2.355723 3.039643 28.21801 37.00765 Oth_NH | .1916496 1.64271 1.273101 1.64271 15.24983 20 Wht_NH | 12.29432 105.3799 81.6694 105.3799 978.2766 1283 | Total | 14.00007 120.0006 93.00049 120.0006 1114.006 1461.008 ----------+----------------------------------------------------------- US native | foreign | 80 | Blk_NH | 23.06076 79.39492 82.03043 101.0061 357.5078 643 Mex_Am | 40.23978 138.5398 143.1386 176.2502 623.8315 1122 Oth_H | 18.47013 63.59002 65.70089 80.89917 286.3398 515 Oth_NH | 7.710831 26.54729 27.42853 33.77344 119.5399 215 Wht_NH | 260.5185 896.928 926.7015 1141.071 4038.781 7264 | Total | 350 1205 1245 1533 5426 9759 ----------+----------------------------------------------------------- US native | foreign | 90 | Blk_NH | 16.2673 72.53712 72.88447 76.82104 221.4901 460 Mex_Am | 37.06116 165.2585 166.0498 175.0184 504.6121 1048 Oth_H | 21.28895 94.92902 95.38359 100.5354 289.8631 602 Oth_NH | 8.169016 36.42625 36.60068 38.57753 111.2265 231 Wht_NH | 198.2136 883.8491 888.0814 936.0477 2698.808 5605 | Total | 281 1253 1259 1327 3826 7946 ----------+----------------------------------------------------------- US native | US native | 70 | Blk_NH | 350.6128 73.86082 96.99885 30.82558 4145.702 4698 Mex_Am | 76.12283 16.03619 21.05977 6.692656 900.0886 1020 Oth_H | 97.01929 20.43828 26.84089 8.529856 1147.172 1300 Oth_NH | 30.07598 6.335868 8.320676 2.644255 355.6232 403 Wht_NH | 4098.169 863.3289 1133.78 360.3076 48457.41 54913 | Total | 4652 980 1287 409 55006 62334 ----------+----------------------------------------------------------- US native | US native | 80 | Blk_NH | 1970.685 760.3871 262.7895 267.0459 22627.09 25888 Mex_Am | 761.311 293.7512 101.5203 103.1646 8741.253 10001 Oth_H | 250.6747 96.7226 33.4273 33.96871 2878.207 3293 Oth_NH | 249.7612 96.37013 33.30548 33.84493 2867.718 3281 Wht_NH | 21769.57 8399.769 2902.957 2949.976 249954.7 285977 | Total | 25002 9647 3334 3388 287069 328440 ----------+----------------------------------------------------------- US native | US native | 90 | Blk_NH | 738.9559 450.2184 161.6596 167.7308 11579.44 13098 Mex_Am | 422.7924 257.5918 92.49329 95.9669 6625.156 7494 Oth_H | 148.9421 90.7449 32.58371 33.8074 2333.922 2640 Oth_NH | 153.3991 93.46037 33.55875 34.81905 2403.763 2719 Wht_NH | 10950.91 6671.984 2395.705 2485.676 171600.7 194105 | Total | 12415 7564 2716 2818 194543 220056 ---------------------------------------------------------------------- . *For each 5x5 table, one needs 9 terms to fit the marginals. For 9 such table > s, we need 81 (9x9) terms to fit the marginals of all of them. . desmat: poisson count meth*mgen*fgen*year feth*mgen*fgen*year ethintct*year*mg > en*fgen --Break-- r(1); . desmat meth*mgen*fgen*year feth*mgen*fgen*year ethintct*year*mgen*fgen Desmat generated the following design matrix: nr Variables Term Parameterization First Last 1 _x_1 _x_4 meth ind(1) 2 _x_5 mgen ind(1) 3 _x_6 _x_9 meth.mgen ind(1).ind(1) 4 _x_10 fgen ind(1) 5 _x_11 _x_13 meth.fgen ind(1).ind(1) 6 _x_14 meth.mgen.fgen ind(1).ind(1).ind(1) 7 _x_15 _x_16 year ind(70) 8 _x_17 _x_23 meth.year ind(1).ind(70) 9 _x_24 mgen.year ind(1).ind(70) 10 _x_25 _x_30 meth.mgen.year ind(1).ind(1).ind(70) 11 _x_31 fgen.year ind(1).ind(70) 12 _x_32 _x_36 meth.fgen.year ind(1).ind(1).ind(70) 13 _x_37 _x_38 mgen.fgen.year ind(1).ind(1).ind(70) 14 _x_39 _x_44 meth.mgen.fgen.year ind(1).ind(1).ind(1).ind(70) 15 _x_45 _x_48 feth ind(1) 16 _x_49 _x_52 feth.mgen ind(1).ind(1) 17 _x_53 _x_55 feth.fgen ind(1).ind(1) 18 _x_56 feth.mgen.fgen ind(1).ind(1).ind(1) 19 _x_57 _x_64 feth.year ind(1).ind(70) 20 _x_65 _x_69 feth.mgen.year ind(1).ind(1).ind(70) 21 _x_70 _x_76 feth.fgen.year ind(1).ind(1).ind(70) 22 _x_77 _x_80 feth.mgen.fgen.year ind(1).ind(1).ind(1).ind(70) 23 _x_81 _x_85 ethintct ind(0) 24 _x_86 _x_95 ethintct.year ind(0).ind(70) 25 _x_96 _x_97 ethintct.mgen ind(0).ind(1) 26 _x_98 _x_104 ethintct.year.mgen ind(0).ind(70).ind(1) 27 _x_105 _x_109 ethintct.fgen ind(0).ind(1) 28 _x_110 _x_118 ethintct.year.fgen ind(0).ind(70).ind(1) 29 _x_119 _x_121 ethintct.mgen.fgen ind(0).ind(1).ind(1) 30 _x_122 _x_125 ethintct.year.mgen.fgen ind(0).ind(70).ind(1).ind(1) . poisson count _x*, difficult Iteration 0: log likelihood = -20876283 (not concave) Iteration 1: log likelihood = -14167330 (not concave) Iteration 2: log likelihood = -8993791.9 (not concave) Iteration 3: log likelihood = -5880730.6 (not concave) Iteration 4: log likelihood = -4926892.4 (not concave) Iteration 5: log likelihood = -4092645.4 (not concave) Iteration 6: log likelihood = -3428563.1 (not concave) Iteration 7: log likelihood = -3311870.8 (not concave) Iteration 8: log likelihood = -3099564.6 (not concave) Iteration 9: log likelihood = -2634429.1 (not concave) Iteration 10: log likelihood = -2435514 (not concave) Iteration 11: log likelihood = -1964247.2 (not concave) Iteration 12: log likelihood = -1520120.1 (not concave) Iteration 13: log likelihood = -1168674.9 Iteration 14: log likelihood = -1168150.1 (backed up) Iteration 15: log likelihood = -1164770.4 (backed up) Iteration 16: log likelihood = -1020708.5 Iteration 17: log likelihood = -78178.033 Iteration 18: log likelihood = -18759.377 Iteration 19: log likelihood = -2472.3502 Iteration 20: log likelihood = -1324.9999 Iteration 21: log likelihood = -1154.6547 Iteration 22: log likelihood = -1142.0003 Iteration 23: log likelihood = -1141.809 Iteration 24: log likelihood = -1141.8087 Iteration 25: log likelihood = -1141.8087 Poisson regression Number of obs = 225 LR chi2(125) = 4502943.68 Prob > chi2 = 0.0000 Log likelihood = -1141.8087 Pseudo R2 = 0.9995 ------------------------------------------------------------------------------ count | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- _x_1 | .9316478 .5716332 1.63 0.103 -.1887326 2.052028 _x_2 | 2.026589 .5402404 3.75 0.000 .9677374 3.085441 _x_3 | 1.460813 .4532053 3.22 0.001 .5725468 2.349079 _x_4 | 2.535714 .564145 4.49 0.000 1.43001 3.641418 _x_5 | 2.070974 .5671875 3.65 0.000 .9593068 3.182641 _x_6 | -1.003417 .451763 -2.22 0.026 -1.888856 -.117978 _x_7 | -1.469252 .441465 -3.33 0.001 -2.334508 -.6039968 _x_8 | -2.4537 .6803145 -3.61 0.000 -3.787091 -1.120308 _x_9 | .4178676 .4960227 0.84 0.400 -.5543191 1.390054 _x_10 | 2.931444 .7745654 3.78 0.000 1.413324 4.449565 _x_11 | 1.077515 .3692022 2.92 0.004 .3538918 1.801138 _x_12 | .5761225 .3320235 1.74 0.083 -.0746316 1.226876 _x_13 | .2991824 .2992435 1.00 0.317 -.287324 .8856888 _x_14 | 1.38097 .5235543 2.64 0.008 .3548227 2.407118 _x_15 | 2.985316 .7870955 3.79 0.000 1.442637 4.527995 _x_16 | 2.532688 .5602012 4.52 0.000 1.434714 3.630662 _x_17 | .2526051 .4572661 0.55 0.581 -.64362 1.14883 _x_18 | -.1242719 .3646337 -0.34 0.733 -.8389409 .5903971 _x_19 | .2666798 .4464477 0.60 0.550 -.6083415 1.141701 _x_20 | -.2938268 .5661067 -0.52 0.604 -1.403376 .8157219 _x_21 | .6081022 .4735247 1.28 0.199 -.3199891 1.536194 _x_22 | .5866592 .7173357 0.82 0.413 -.8192929 1.992611 _x_23 | -.4863716 .278773 -1.74 0.081 -1.032757 .0600136 _x_24 | 1.184573 .9520553 1.24 0.213 -.6814212 3.050567 _x_25 | -.5448379 .5830132 -0.93 0.350 -1.687523 .5978469 _x_26 | -1.598491 .5553013 -2.88 0.004 -2.686861 -.5101201 _x_27 | -.6522824 .4590753 -1.42 0.155 -1.552053 .2474886 _x_28 | -.7317568 .7071676 -1.03 0.301 -2.11778 .6542662 _x_29 | -.3265006 .4886545 -0.67 0.504 -1.284246 .6312447 _x_30 | -.6209193 .2768357 -2.24 0.025 -1.163507 -.0783312 _x_31 | -.6906914 .9675439 -0.71 0.475 -2.587042 1.20566 _x_32 | .3054864 .5814557 0.53 0.599 -.8341458 1.445119 _x_33 | .1283697 .353 0.36 0.716 -.5634976 .8202369 _x_34 | -.2332816 .5422301 -0.43 0.667 -1.296033 .8294698 _x_35 | -.221222 .5016435 -0.44 0.659 -1.204425 .7619813 _x_36 | -.1992251 .5711021 -0.35 0.727 -1.318565 .9201145 _x_37 | -.1708014 .5939701 -0.29 0.774 -1.334961 .9933585 _x_38 | -1.548676 .7929245 -1.95 0.051 -3.10278 .0054272 _x_39 | .1864345 .3815681 0.49 0.625 -.5614252 .9342942 _x_40 | -.2917444 .4691436 -0.62 0.534 -1.211249 .6277601 _x_41 | .58862 .3516736 1.67 0.094 -.1006475 1.277887 _x_42 | .1129533 .5421289 0.21 0.835 -.9495999 1.175507 _x_43 | .6385824 .589278 1.08 0.279 -.5163813 1.793546 _x_44 | .543646 .517329 1.05 0.293 -.4703001 1.557592 _x_45 | 2.388981 .8486406 2.82 0.005 .7256755 4.052286 _x_46 | 3.388014 .8312864 4.08 0.000 1.758722 5.017305 _x_47 | -.1698373 .5045383 -0.34 0.736 -1.158714 .8190396 _x_48 | 3.637316 .8461789 4.30 0.000 1.978836 5.295796 _x_49 | .6989502 .4441106 1.57 0.116 -.1714906 1.569391 _x_50 | .3474361 .422239 0.82 0.411 -.4801372 1.175009 _x_51 | 4.102716 .8742149 4.69 0.000 2.389287 5.816146 _x_52 | .8065551 .3954879 2.04 0.041 .0314131 1.581697 _x_53 | -1.647956 .7384647 -2.23 0.026 -3.095321 -.2005922 _x_54 | -2.056851 .7309126 -2.81 0.005 -3.489413 -.6242886 _x_55 | -.5706755 .7646251 -0.75 0.455 -2.069313 .9279622 _x_56 | -2.919955 .7308575 -4.00 0.000 -4.35241 -1.487501 _x_57 | -.502014 .7577015 -0.66 0.508 -1.987082 .9830538 _x_58 | -.9818586 .8717225 -1.13 0.260 -2.690403 .7266862 _x_59 | -.6824774 .8722184 -0.78 0.434 -2.391994 1.027039 _x_60 | -1.033672 .7305388 -1.41 0.157 -2.465502 .3981578 _x_61 | .0668824 .9265136 0.07 0.942 -1.749051 1.882816 _x_62 | -.798168 .9123228 -0.87 0.382 -2.586288 .9899519 _x_63 | -.3140568 .7829867 -0.40 0.688 -1.848682 1.220569 _x_64 | -.0097322 .3782829 -0.03 0.979 -.7511531 .7316886 _x_65 | -.1238172 .4632769 -0.27 0.789 -1.031823 .7841888 _x_66 | .5959455 .4462892 1.34 0.182 -.2787653 1.470656 _x_67 | .1336854 .5480509 0.24 0.807 -.9404746 1.207845 _x_68 | -.0396588 .549671 -0.07 0.942 -1.116994 1.037676 _x_69 | -1.552349 .8541877 -1.82 0.069 -3.226526 .1218284 _x_70 | .9900426 .8730691 1.13 0.257 -.7211413 2.701227 _x_71 | 1.544971 .7553059 2.05 0.041 .0645985 3.025343 _x_72 | .0084517 .7657018 0.01 0.991 -1.492296 1.5092 _x_73 | .6061061 .8411451 0.72 0.471 -1.042508 2.25472 _x_74 | .4085777 .7653378 0.53 0.593 -1.091457 1.908612 _x_75 | 1.255771 .7467873 1.68 0.093 -.2079051 2.719447 _x_76 | .3255401 .8690779 0.37 0.708 -1.377821 2.028901 _x_77 | .0407735 .4621546 0.09 0.930 -.8650329 .9465799 _x_78 | .0720746 .4454441 0.16 0.871 -.8009798 .945129 _x_79 | .3930481 .4132311 0.95 0.342 -.41687 1.202966 _x_80 | 1.775733 .7841982 2.26 0.024 .238733 3.312733 _x_81 | 4.892832 .8069098 6.06 0.000 3.311318 6.474346 _x_82 | 3.303614 .4970788 6.65 0.000 2.329358 4.277871 _x_83 | -1.809186 .5306139 -3.41 0.001 -2.84917 -.7692018 _x_84 | 2.175983 .5439925 4.00 0.000 1.109778 3.242189 _x_85 | 1.997963 .2651152 7.54 0.000 1.478347 2.517579 _x_86 | 1.20026 1.04956 1.14 0.253 -.8568395 3.257359 _x_87 | .0010089 .5974948 0.00 0.999 -1.170059 1.172077 _x_88 | .3014835 .3578005 0.84 0.399 -.3997925 1.00276 _x_89 | -.0403999 .358016 -0.11 0.910 -.7420983 .6612986 _x_90 | 3.835774 .556273 6.90 0.000 2.745499 4.926049 _x_91 | 3.720932 .5545422 6.71 0.000 2.634049 4.807815 _x_92 | -.9672232 .7936603 -1.22 0.223 -2.522769 .5883225 _x_93 | -.8274924 .7937978 -1.04 0.297 -2.383307 .7283227 _x_94 | -.490884 .2775622 -1.77 0.077 -1.034896 .0531279 _x_95 | .2765865 .4270312 0.65 0.517 -.5603792 1.113552 _x_96 | .4188832 .3600085 1.16 0.245 -.2867205 1.124487 _x_97 | 2.409232 .3543459 6.80 0.000 1.714726 3.103737 _x_98 | -.8744245 .6290336 -1.39 0.164 -2.107308 .3584587 _x_99 | -.7650971 1.018462 -0.75 0.453 -2.761246 1.231052 _x_100 | -1.893693 .373711 -5.07 0.000 -2.626153 -1.161232 _x_101 | -1.767451 .3723229 -4.75 0.000 -2.49719 -1.037711 _x_102 | .1941561 .5565234 0.35 0.727 -.8966098 1.284922 _x_103 | .0424446 .5582661 0.08 0.939 -1.051737 1.136626 _x_104 | -.7361726 .3218828 -2.29 0.022 -1.367051 -.1052939 _x_105 | -.1265012 .9902645 -0.13 0.898 -2.067384 1.814381 _x_106 | -.0636946 .364272 -0.17 0.861 -.7776545 .6502653 _x_107 | 2.978115 .4122843 7.22 0.000 2.170053 3.786177 _x_108 | .7195507 .7496942 0.96 0.337 -.7498229 2.188924 _x_109 | .2982343 .3914758 0.76 0.446 -.4690441 1.065513 _x_110 | -.7709607 .8615851 -0.89 0.371 -2.459637 .9177152 _x_111 | -.4104228 .4995436 -0.82 0.411 -1.38951 .5686647 _x_112 | -.268919 .4996858 -0.54 0.590 -1.248285 .7104473 _x_113 | -2.835861 .4314424 -6.57 0.000 -3.681472 -1.990249 _x_114 | -2.774999 .430981 -6.44 0.000 -3.619706 -1.930291 _x_115 | -.1672161 .5871955 -0.28 0.776 -1.318098 .9836659 _x_116 | -.3430463 .5860953 -0.59 0.558 -1.491772 .8056794 _x_117 | .2769042 .4095818 0.68 0.499 -.5258613 1.07967 _x_118 | -.5341803 .3016849 -1.77 0.077 -1.125472 .0571113 _x_119 | 3.143092 .6015973 5.22 0.000 1.963983 4.322201 _x_120 | .729016 .5369992 1.36 0.175 -.323483 1.781515 _x_121 | .9571745 .3063871 3.12 0.002 .3566669 1.557682 _x_122 | -.4443595 .8465881 -0.52 0.600 -2.103642 1.214923 _x_123 | -.1958282 .3718976 -0.53 0.598 -.9247341 .5330778 _x_124 | -.2950862 .372183 -0.79 0.428 -1.024552 .4343791 _x_125 | -.4691162 .3206613 -1.46 0.143 -1.097601 .1593684 _cons | -4.4789 .9431181 -4.75 0.000 -6.327377 -2.630422 ------------------------------------------------------------------------------ . poisgof Goodness-of-fit chi2 = 951.6173 Prob > chi2(99) = 0.0000 . desrep ------------------------------------------------------------------------------- poisson ------------------------------------------------------------------------------- Dependent variable count Number of observations: 225 Initial log likelihood: -2252613.647 Log likelihood: -1141.809 LR chi square: 4502943.678 Model degrees of freedom: 125 Pseudo R-squared: 0.999 Prob: 0.000 ------------------------------------------------------------------------------- nr Effect Coeff s.e. ------------------------------------------------------------------------------- count meth 1 Mex_Am 0.932 0.572 2 Oth_H 2.027** 0.540 3 Oth_NH 1.461** 0.453 4 Wht_NH 2.536** 0.564 mgen 5 US native 2.071** 0.567 meth.mgen 6 Mex_Am.US native -1.003* 0.452 7 Oth_H.US native -1.469** 0.441 8 Oth_NH.US native -2.454** 0.680 9 Wht_NH.US native 0.418 0.496 fgen 10 US native 2.931** 0.775 meth.fgen 11 Mex_Am.US native 1.078** 0.369 12 Oth_H.US native 0.576 0.332 13 Wht_NH.US native 0.299 0.299 meth.mgen.fgen 14 Oth_NH.US native.US native 1.381** 0.524 year 15 80 2.985** 0.787 16 90 2.533** 0.560 meth.year 17 Mex_Am.80 0.253 0.457 18 Mex_Am.90 -0.124 0.365 19 Oth_H.80 0.267 0.446 20 Oth_H.90 -0.294 0.566 21 Oth_NH.80 0.608 0.474 22 Oth_NH.90 0.587 0.717 23 Wht_NH.90 -0.486 0.279 mgen.year 24 US native.90 1.185 0.952 meth.mgen.year 25 Mex_Am.US native.80 -0.545 0.583 26 Oth_H.US native.80 -1.598** 0.555 27 Oth_H.US native.90 -0.652 0.459 28 Oth_NH.US native.80 -0.732 0.707 29 Oth_NH.US native.90 -0.327 0.489 30 Wht_NH.US native.80 -0.621* 0.277 fgen.year 31 US native.80 -0.691 0.968 meth.fgen.year 32 Mex_Am.US native.90 0.305 0.581 33 Oth_H.US native.90 0.128 0.353 34 Oth_NH.US native.90 -0.233 0.542 35 Wht_NH.US native.80 -0.221 0.502 36 Wht_NH.US native.90 -0.199 0.571 mgen.fgen.year 37 US native.US native.80 -0.171 0.594 38 US native.US native.90 -1.549 0.793 meth.mgen.fgen.year 39 Mex_Am.US native.US native.80 0.186 0.382 40 Mex_Am.US native.US native.90 -0.292 0.469 41 Oth_H.US native.US native.80 0.589 0.352 42 Oth_NH.US native.US native.80 0.113 0.542 43 Wht_NH.US native.US native.80 0.639 0.589 44 Wht_NH.US native.US native.90 0.544 0.517 feth 45 Mex_Am 2.389** 0.849 46 Oth_H 3.388** 0.831 47 Oth_NH -0.170 0.505 48 Wht_NH 3.637** 0.846 feth.mgen 49 Mex_Am.US native 0.699 0.444 50 Oth_H.US native 0.347 0.422 51 Oth_NH.US native 4.103** 0.874 52 Wht_NH.US native 0.807* 0.395 feth.fgen 53 Mex_Am.US native -1.648* 0.738 54 Oth_H.US native -2.057** 0.731 55 Wht_NH.US native -0.571 0.765 feth.mgen.fgen 56 Oth_NH.US native.US native -2.920** 0.731 feth.year 57 Mex_Am.80 -0.502 0.758 58 Mex_Am.90 -0.982 0.872 59 Oth_H.80 -0.682 0.872 60 Oth_H.90 -1.034 0.731 61 Oth_NH.80 0.067 0.927 62 Oth_NH.90 -0.798 0.912 63 Wht_NH.80 -0.314 0.783 64 Wht_NH.90 -0.010 0.378 feth.mgen.year 65 Mex_Am.US native.90 -0.124 0.463 66 Oth_H.US native.80 0.596 0.446 67 Oth_NH.US native.80 0.134 0.548 68 Oth_NH.US native.90 -0.040 0.550 69 Wht_NH.US native.90 -1.552 0.854 feth.fgen.year 70 Mex_Am.US native.80 0.990 0.873 71 Mex_Am.US native.90 1.545* 0.755 72 Oth_H.US native.80 0.008 0.766 73 Oth_H.US native.90 0.606 0.841 74 Oth_NH.US native.80 0.409 0.765 75 Oth_NH.US native.90 1.256 0.747 76 Wht_NH.US native.80 0.326 0.869 feth.mgen.fgen.year 77 Mex_Am.US native.US native.80 0.041 0.462 78 Oth_H.US native.US native.90 0.072 0.445 79 Wht_NH.US native.US native.80 0.393 0.413 80 Wht_NH.US native.US native.90 1.776* 0.784 ethintct 81 1 4.893** 0.807 82 2 3.304** 0.497 83 3 -1.809** 0.531 84 4 2.176** 0.544 85 5 1.998** 0.265 ethintct.year 86 1.80 1.200 1.050 87 1.90 0.001 0.597 88 2.80 0.301 0.358 89 2.90 -0.040 0.358 90 3.80 3.836** 0.556 91 3.90 3.721** 0.555 92 4.80 -0.967 0.794 93 4.90 -0.827 0.794 94 5.80 -0.491 0.278 95 5.90 0.277 0.427 ethintct.mgen 96 2.US native 0.419 0.360 97 3.US native 2.409** 0.354 ethintct.year.mgen 98 1.80.US native -0.874 0.629 99 1.90.US native -0.765 1.018 100 3.80.US native -1.894** 0.374 101 3.90.US native -1.767** 0.372 102 4.80.US native 0.194 0.557 103 4.90.US native 0.042 0.558 104 5.90.US native -0.736* 0.322 ethintct.fgen 105 1.US native -0.127 0.990 106 2.US native -0.064 0.364 107 3.US native 2.978** 0.412 108 4.US native 0.720 0.750 109 5.US native 0.298 0.391 ethintct.year.fgen 110 1.80.US native -0.771 0.862 111 2.80.US native -0.410 0.500 112 2.90.US native -0.269 0.500 113 3.80.US native -2.836** 0.431 114 3.90.US native -2.775** 0.431 115 4.80.US native -0.167 0.587 116 4.90.US native -0.343 0.586 117 5.80.US native 0.277 0.410 118 5.90.US native -0.534 0.302 ethintct.mgen.fgen 119 1.US native.US native 3.143** 0.602 120 4.US native.US native 0.729 0.537 121 5.US native.US native 0.957** 0.306 ethintct.year.mgen.fgen 122 1.90.US native.US native -0.444 0.847 123 2.80.US native.US native -0.196 0.372 124 2.90.US native.US native -0.295 0.372 125 5.80.US native.US native -0.469 0.321 126 _cons -4.479** 0.943 ------------------------------------------------------------------------------- * p < .05 ** p < .01 . poisgof Goodness-of-fit chi2 = 951.6173 Prob > chi2(99) = 0.0000 . *It took an additional 45 terms to fit the endogamy diagonal of each table. . predict marginals_and_diagonal_by9 (option n assumed; predicted number of events) . table meth feth , by(mgen fgen year) contents (sum marginals_and_diagonal_by9 > ) row col ---------------------------------------------------------------------- mgen, | fgen, | year and | feth meth | Blk_NH Mex_Am Oth_H Oth_NH Wht_NH Total ----------+----------------------------------------------------------- foreign | foreign | 70 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------------------- foreign | foreign | 80 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------------------- foreign | foreign | 90 | Blk_NH | Mex_Am | Oth_H | Oth_NH | Wht_NH | | Total | ----------+----------------------------------------------------------- foreign | US native | 70 | Blk_NH | 25 .4464485 .8054996 .1795516 4.5685 31 Mex_Am | 1.586781 85 6.006667 1.338929 34.06762 128 Oth_H | 2.872711 6.027187 35 2.424 61.6761 108 Oth_NH | .9170048 1.923952 3.471269 13.99996 19.68777 39.99996 Wht_NH | 3.623503 7.602412 13.71656 3.05752 773 801 | Total | 34 101 59 20.99996 893 1108 ----------+----------------------------------------------------------- foreign | US native | 80 | Blk_NH | 381 7.215432 4.072701 2.865641 45.84623 441 Mex_Am | 20.26584 1586 39.0981 27.51028 440.1258 2113 Oth_H | 37.20937 127.1813 628 50.51061 808.0988 1651 Oth_NH | 16.71129 57.11902 32.24043 132 362.9293 601 Wht_NH | 28.8135 98.48427 55.58876 39.11347 5020 5242 | Total | 484 1876 759 252 6677 10048 ----------+----------------------------------------------------------- foreign | US native | 90 | Blk_NH | 315 9.868709 6.611626 3.571546 56.94812 392 Mex_Am | 23.94141 1653 59.09857 31.92456 509.0355 2277 Oth_H | 30.64553 112.9137 627 40.86414 651.5767 1463 Oth_NH | 16.43516 60.55545 40.56964 123 349.4397 590 Wht_NH | 22.97789 84.66219 56.72016 30.63976 3752 3947 | Total | 409 1921 790 230 5319 8669 ----------+----------------------------------------------------------- US native | foreign | 70 | Blk_NH | 12 1.973888 3.771693 4.59493 7.659489 30 Mex_Am | .0837688 76 3.510487 4.27671 7.129035 91 Oth_H | .1571446 3.44644 12 8.022822 13.37359 37 Oth_NH | .0333462 .7313365 1.397434 15 2.837884 20 Wht_NH | 1.72574 37.84834 72.32039 88.10554 1083 1283 | Total | 14 120 93 120 1114 1461 ----------+----------------------------------------------------------- US native | foreign | 80 | Blk_NH | 329 23.64867 68.46401 111.1452 110.7421 643 Mex_Am | 1.237865 919 47.57494 77.23363 76.95357 1122 Oth_H | .8211219 10.90077 401 51.23194 51.04617 515 Oth_NH | .5832433 7.742819 22.41582 148 36.25812 215 Wht_NH | 18.35777 243.7077 705.5452 1145.389 5151 7264 | Total | 350 1205 1245 1533 5426 9759 ----------+----------------------------------------------------------- US native | foreign | 90 | Blk_NH | 230 26.88558 55.20829 81.80901 66.09711 460 Mex_Am | 3.044369 878 45.38001 67.24523 54.33039 1048 Oth_H | 2.510703 18.22543 481 55.45739 44.80648 602 Oth_NH | 1.779989 12.92111 26.53289 158 31.76602 231 Wht_NH | 43.66494 316.9679 650.8788 964.4883 3629 5605 | Total | 281 1253 1259 1327 3826 7946 ----------+----------------------------------------------------------- US native | US native | 70 | Blk_NH | 4596 7.124168 9.044144 4.648026 81.18366 4698 Mex_Am | 4.614779 756 24.72618 12.70744 221.9516 1020 Oth_H | 5.24344 22.1304 1006 14.43855 252.1876 1300 Oth_NH | 2.488306 10.50211 13.33245 257 119.6771 403 Wht_NH | 43.65348 184.2433 233.8972 120.206 54331 54913 | Total | 4652 980 1287 409 55006 62334 ----------+----------------------------------------------------------- US native | US native | 80 | Blk_NH | 24628 101.1008 69.95558 71.47953 1017.464 25888 Mex_Am | 34.71906 7116 172.0538 175.802 2502.425 10001 Oth_H | 20.85534 149.3641 1514 105.6022 1503.178 3293 Oth_NH | 20.58832 147.4517 102.0275 1527 1483.932 3281 Wht_NH | 297.8373 2133.083 1475.963 1508.116 280562 285977 | Total | 25002 9647 3334 3388 287069 328440 ----------+----------------------------------------------------------- US native | US native | 90 | Blk_NH | 12005 96.67671 55.43499 61.74243 879.1459 13098 Mex_Am | 36.13705 5019 135.6973 151.137 2152.029 7494 Oth_H | 20.24328 132.5675 1197 84.66405 1205.525 2640 Oth_NH | 22.3553 146.3986 83.94581 1135 1331.3 2719 Wht_NH | 331.2644 2169.357 1243.922 1385.457 188975 194105 | Total | 12415 7564 2716 2818 194543 220056 ---------------------------------------------------------------------- . *This model doesn't fit too badly, in fact. . *What's the BIC? . poisgof Goodness-of-fit chi2 = 951.6173 Prob > chi2(99) = 0.0000 . display 951.5-(99*ln(649821)) -373.56077 . *What the (parsimony favoring) BIC says, is that the model which fits only the > marginals and the diagonal of each of these 9 tables fits the data fairly wel > l. . desmat meth*year*mgen*fgen*ethintct Desmat generated the following design matrix: nr Variables Term Parameterization First Last 1 _x_1 _x_4 meth ind(1) 2 _x_5 _x_6 year ind(70) 3 _x_7 _x_14 meth.year ind(1).ind(70) 4 _x_15 mgen ind(1) 5 _x_16 _x_19 meth.mgen ind(1).ind(1) 6 _x_20 year.mgen ind(70).ind(1) 7 _x_21 _x_26 meth.year.mgen ind(1).ind(70).ind(1) 8 _x_27 fgen ind(1) 9 _x_28 _x_30 meth.fgen ind(1).ind(1) 10 _x_31 year.fgen ind(70).ind(1) 11 _x_32 _x_36 meth.year.fgen ind(1).ind(70).ind(1) 12 _x_37 meth.mgen.fgen ind(1).ind(1).ind(1) 13 _x_38 _x_39 year.mgen.fgen ind(70).ind(1).ind(1) 14 _x_40 _x_44 meth.year.mgen.fgen ind(1).ind(70).ind(1).ind(1) 15 _x_45 _x_49 ethintct ind(0) 16 _x_50 _x_59 year.ethintct ind(70).ind(0) 17 _x_60 mgen.ethintct ind(1).ind(0) 18 _x_61 _x_67 year.mgen.ethintct ind(70).ind(1).ind(0) 19 _x_68 _x_72 fgen.ethintct ind(1).ind(0) 20 _x_73 _x_78 year.fgen.ethintct ind(70).ind(1).ind(0) 21 _x_79 _x_82 mgen.fgen.ethintct ind(1).ind(1).ind(0) 22 _x_83 _x_89 year.mgen.fgen.ethintct ind(70).ind(1).ind(1).ind(0) . exit, clear