log type: text
opened on: 2 Nov 2005, 11:21:11
. use "C:\AAA Miker Files\current class files\methods tabular arrays\HW3 dataset with best f
> it vars.dta", clear
. desmat: poisson count meth*mgen*fgen*year feth*fgen*mgen*year ethintct*mgen*fgen, verbose
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.fgen ind(1).ind(1)
17 _x_53 _x_55 feth.mgen ind(1).ind(1)
18 _x_56 feth.fgen.mgen ind(1).ind(1).ind(1)
19 _x_57 _x_64 feth.year ind(1).ind(70)
20 _x_65 _x_71 feth.fgen.year ind(1).ind(1).ind(70)
21 _x_72 _x_76 feth.mgen.year ind(1).ind(1).ind(70)
22 _x_77 _x_80 feth.fgen.mgen.year ind(1).ind(1).ind(1).ind(70)
23 _x_81 _x_85 ethintct ind(0)
24 _x_86 _x_87 ethintct.mgen ind(0).ind(1)
25 _x_88 _x_92 ethintct.fgen ind(0).ind(1)
26 _x_93 _x_95 ethintct.mgen.fgen ind(0).ind(1).ind(1)
Iteration 0: log likelihood = -11376909 (not concave)
Iteration 1: log likelihood = -10466756 (not concave)
Iteration 2: log likelihood = -8792075 (not concave)
Iteration 3: log likelihood = -8616233.5 (not concave)
Iteration 4: log likelihood = -8065096.4 (not concave)
Iteration 5: log likelihood = -7961919.7 (not concave)
Iteration 6: log likelihood = -7798948.8 (not concave)
Iteration 7: log likelihood = -7671253 (not concave)
Iteration 8: log likelihood = -6867511.8 (not concave)
Iteration 9: log likelihood = -6597600 (not concave)
Iteration 10: log likelihood = -6499953.5 (not concave)
Iteration 11: log likelihood = -5554773.7 (not concave)
Iteration 12: log likelihood = -5126268.2 (not concave)
Iteration 13: log likelihood = -4609377.9 (not concave)
Iteration 14: log likelihood = -4297553.4 (not concave)
Iteration 15: log likelihood = -4120374.4 (not concave)
Iteration 16: log likelihood = -4028082.3 (not concave)
Iteration 17: log likelihood = -3921242.2 (not concave)
Iteration 18: log likelihood = -3840765.5 (not concave)
Iteration 19: log likelihood = -3735575.7 (not concave)
Iteration 20: log likelihood = -3656015.1 (not concave)
Iteration 21: log likelihood = -3584493.2 (not concave)
Iteration 22: log likelihood = -3425554.7 (not concave)
Iteration 23: log likelihood = -3352914.4 (not concave)
Iteration 24: log likelihood = -2993396.8 (not concave)
Iteration 25: log likelihood = -2832396.9 (not concave)
Iteration 26: log likelihood = -2785085.5 (not concave)
Iteration 27: log likelihood = -2693097.7 (not concave)
Iteration 28: log likelihood = -2632519.3 (not concave)
Iteration 29: log likelihood = -2569831.1 (not concave)
Iteration 30: log likelihood = -2486063.7 (not concave)
Iteration 31: log likelihood = -2394807 (not concave)
Iteration 32: log likelihood = -2306582.8 (not concave)
Iteration 33: log likelihood = -2267532.2 (not concave)
Iteration 34: log likelihood = -2195187.3 (not concave)
Iteration 35: log likelihood = -2150257.3 (not concave)
Iteration 36: log likelihood = -2130879.5 (not concave)
Iteration 37: log likelihood = -2108295.3 (not concave)
Iteration 38: log likelihood = -2088083.3 (not concave)
Iteration 39: log likelihood = -2067160.3 (not concave)
Iteration 40: log likelihood = -2043147.9 (not concave)
Iteration 41: log likelihood = -2030737.4 (not concave)
Iteration 42: log likelihood = -1998531.4 (not concave)
Iteration 43: log likelihood = -1963388.5 (not concave)
Iteration 44: log likelihood = -1951469.2 (not concave)
Iteration 45: log likelihood = -1940128.6 (not concave)
Iteration 46: log likelihood = -1919640.4 (not concave)
Iteration 47: log likelihood = -1903447.1 (not concave)
Iteration 48: log likelihood = -1887414.4 (not concave)
Iteration 49: log likelihood = -1876388.6 (not concave)
Iteration 50: log likelihood = -1865797.7 (not concave)
Iteration 51: log likelihood = -1853554.1 (not concave)
Iteration 52: log likelihood = -1833665.8 (not concave)
Iteration 53: log likelihood = -1806849.3 (not concave)
Iteration 54: log likelihood = -1778337.2 (not concave)
Iteration 55: log likelihood = -1769701.3 (not concave)
Iteration 56: log likelihood = -1760748.9 (not concave)
Iteration 57: log likelihood = -1641141.4 (not concave)
Iteration 58: log likelihood = -1576855.8 (not concave)
Iteration 59: log likelihood = -1552005.9 (not concave)
Iteration 60: log likelihood = -1540388.5 (not concave)
Iteration 61: log likelihood = -1529773.7 (not concave)
Iteration 62: log likelihood = -1521730.9 (not concave)
Iteration 63: log likelihood = -1514350.9 (not concave)
Iteration 64: log likelihood = -1507481.4 (not concave)
Iteration 65: log likelihood = -1500400.9 (not concave)
Iteration 66: log likelihood = -1493536.1 (not concave)
Iteration 67: log likelihood = -1486779.5 (not concave)
Iteration 68: log likelihood = -1480150 (not concave)
Iteration 69: log likelihood = -1473483.9 (not concave)
Iteration 70: log likelihood = -1466942.5 (not concave)
Iteration 71: log likelihood = -1460384.7 (not concave)
Iteration 72: log likelihood = -1453922.3 (not concave)
Iteration 73: log likelihood = -1447426.3 (not concave)
Iteration 74: log likelihood = -1441019.9 (not concave)
Iteration 75: log likelihood = -1434575.9 (not concave)
Iteration 76: log likelihood = -1428211.3 (not concave)
Iteration 77: log likelihood = -1421805.4 (not concave)
Iteration 78: log likelihood = -1415474.9 (not concave)
Iteration 79: log likelihood = -1409100.7 (not concave)
Iteration 80: log likelihood = -1402797.7 (not concave)
Iteration 81: log likelihood = -1396449.6 (not concave)
Iteration 82: log likelihood = -1390170.5 (not concave)
Iteration 83: log likelihood = -1383845.1 (not concave)
Iteration 84: log likelihood = -1377586.7 (not concave)
Iteration 85: log likelihood = -1371281.3 (not concave)
Iteration 86: log likelihood = -1365041.3 (not concave)
Iteration 87: log likelihood = -1358753.8 (not concave)
Iteration 88: log likelihood = -1352530.4 (not concave)
Iteration 89: log likelihood = -1346259.1 (not concave)
Iteration 90: log likelihood = -1340050.7 (not concave)
Iteration 91: log likelihood = -1333794.2 (not concave)
Iteration 92: log likelihood = -1327599.6 (not concave)
Iteration 93: log likelihood = -1321356.7 (not concave)
Iteration 94: log likelihood = -1315175.1 (not concave)
Iteration 95: log likelihood = -1308945 (not concave)
Iteration 96: log likelihood = -1302775.9 (not concave)
Iteration 97: log likelihood = -1296558.6 (not concave)
Iteration 98: log likelihood = -1290402 (not concave)
Iteration 99: log likelihood = -1284197.6 (not concave)
Iteration 100: log likelihood = -1278054.2 (not concave)
Iteration 101: log likelihood = -1271863.7 (not concave)
Iteration 102: log likelihood = -1265734.8 (not concave)
Iteration 103: log likelihood = -1259560 (not concave)
Iteration 104: log likelihood = -1253447.8 (not concave)
Iteration 105: log likelihood = -1247291.5 (not concave)
Iteration 106: log likelihood = -1241199.5 (not concave)
Iteration 107: log likelihood = -1235065.9 (not concave)
Iteration 108: log likelihood = -1228999 (not concave)
Iteration 109: log likelihood = -1222894 (not concave)
Iteration 110: log likelihood = -1216859.2 (not concave)
Iteration 111: log likelihood = -1210790.6 (not concave)
Iteration 112: log likelihood = -1204796.5 (not concave)
Iteration 113: log likelihood = -1198773.7 (not concave)
Iteration 114: log likelihood = -1192829.3 (not concave)
Iteration 115: log likelihood = -1186860.7 (not concave)
Iteration 116: log likelihood = -1180972.4 (not concave)
Iteration 117: log likelihood = -1175061.7 (not concave)
Iteration 118: log likelihood = -1169229.6 (not concave)
Iteration 119: log likelihood = -1163373.2 (not concave)
Iteration 120: log likelihood = -1157589.9 (not concave)
Iteration 121: log likelihood = -1151777.7 (not concave)
Iteration 122: log likelihood = -1146032.1 (not concave)
Iteration 123: log likelihood = -1140252.6 (not concave)
Iteration 124: log likelihood = -1134534.1 (not concave)
Iteration 125: log likelihood = -1128778 (not concave)
Iteration 126: log likelihood = -1123079.3 (not concave)
Iteration 127: log likelihood = -1117341 (not concave)
Iteration 128: log likelihood = -1111658.2 (not concave)
Iteration 129: log likelihood = -1105934.8 (not concave)
Iteration 130: log likelihood = -1100266 (not concave)
Iteration 131: log likelihood = -1094556.6 (not concave)
Iteration 132: log likelihood = -1088901.7 (not concave)
Iteration 133: log likelihood = -1083206.6 (not concave)
Iteration 134: log likelihood = -1077566.4 (not concave)
Iteration 135: log likelihood = -1071887 (not concave)
Iteration 136: log likelihood = -1066263.4 (not concave)
Iteration 137: log likelihood = -1060602.2 (not concave)
Iteration 138: log likelihood = -1054998.3 (not concave)
Iteration 139: log likelihood = -1049359.1 (not concave)
Iteration 140: log likelihood = -1043779.9 (not concave)
Iteration 141: log likelihood = -1038169 (not concave)
Iteration 142: log likelihood = -1032621.9 (not concave)
Iteration 143: log likelihood = -1027048.1 (not concave)
Iteration 144: log likelihood = -1021543.1 (not concave)
Iteration 145: log likelihood = -1016017.9 (not concave)
Iteration 146: log likelihood = -1010567.4 (not concave)
Iteration 147: log likelihood = -1005103.5 (not concave)
Iteration 148: log likelihood = -999719.88 (not concave)
Iteration 149: log likelihood = -994329.22 (not concave)
Iteration 150: log likelihood = -989022.56 (not concave)
Iteration 151: log likelihood = -983713.1 (not concave)
Iteration 152: log likelihood = -978488.27 (not concave)
Iteration 153: log likelihood = -973261.91 (not concave)
Iteration 154: log likelihood = -968117.49 (not concave)
Iteration 155: log likelihood = -962969.8 (not concave)
Iteration 156: log likelihood = -957898.77 (not concave)
Iteration 157: log likelihood = -952820.6 (not concave)
Iteration 158: log likelihood = -947812.58 (not concave)
Iteration 159: log likelihood = -942792.61 (not concave)
Iteration 160: log likelihood = -937836.28 (not concave)
Iteration 161: log likelihood = -932863.24 (not concave)
Iteration 162: log likelihood = -927948.14 (not concave)
Iteration 163: log likelihood = -923012.16 (not concave)
Iteration 164: log likelihood = -918129.46 (not concave)
Iteration 165: log likelihood = -913222.54 (not concave)
Iteration 166: log likelihood = -908365.26 (not concave)
Iteration 167: log likelihood = -903481.19 (not concave)
Iteration 168: log likelihood = -898643.99 (not concave)
Iteration 169: log likelihood = -893778.06 (not concave)
Iteration 170: log likelihood = -888956.93 (not concave)
Iteration 171: log likelihood = -884105.63 (not concave)
Iteration 172: log likelihood = -879297.57 (not concave)
Iteration 173: log likelihood = -874458.26 (not concave)
Iteration 174: log likelihood = -869661.01 (not concave)
Iteration 175: log likelihood = -864831.7 (not concave)
Iteration 176: log likelihood = -860043.53 (not concave)
Iteration 177: log likelihood = -855222.71 (not concave)
Iteration 178: log likelihood = -850442.29 (not concave)
Iteration 179: log likelihood = -845628.75 (not concave)
Iteration 180: log likelihood = -840855.03 (not concave)
Iteration 181: log likelihood = -836047.84 (not concave)
Iteration 182: log likelihood = -831280.01 (not concave)
Iteration 183: log likelihood = -826478.41 (not concave)
Iteration 184: log likelihood = -821715.79 (not concave)
Iteration 185: log likelihood = -816919.2 (not concave)
Iteration 186: log likelihood = -812161.28 (not concave)
Iteration 187: log likelihood = -807369.23 (not concave)
Iteration 188: log likelihood = -802615.61 (not concave)
Iteration 189: log likelihood = -797827.76 (not concave)
Iteration 190: log likelihood = -793078.17 (not concave)
Iteration 191: log likelihood = -788294.31 (not concave)
Iteration 192: log likelihood = -783548.6 (not concave)
Iteration 193: log likelihood = -778768.67 (not concave)
Iteration 194: log likelihood = -774026.87 (not concave)
Iteration 195: log likelihood = -769250.96 (not concave)
Iteration 196: log likelihood = -764513.28 (not concave)
Iteration 197: log likelihood = -759741.74 (not concave)
Iteration 198: log likelihood = -755008.65 (not concave)
Iteration 199: log likelihood = -750242.13 (not concave)
Iteration 200: log likelihood = -745514.48 (not concave)
Iteration 201: log likelihood = -740754.06 (not concave)
Iteration 202: log likelihood = -736033.21 (not concave)
Iteration 203: log likelihood = -731280.6 (not concave)
Iteration 204: log likelihood = -726568.66 (not concave)
Iteration 205: log likelihood = -721826.45 (not concave)
Iteration 206: log likelihood = -717126.54 (not concave)
Iteration 207: log likelihood = -712398.58 (not concave)
Iteration 208: log likelihood = -707715.33 (not concave)
Iteration 209: log likelihood = -703007.2 (not concave)
Iteration 210: log likelihood = -698347.27 (not concave)
Iteration 211: log likelihood = -693666.97 (not concave)
Iteration 212: log likelihood = -689039.77 (not concave)
Iteration 213: log likelihood = -684398.46 (not concave)
Iteration 214: log likelihood = -679816.93 (not concave)
Iteration 215: log likelihood = -675229.7 (not concave)
Iteration 216: log likelihood = -670710.97 (not concave)
Iteration 217: log likelihood = -666197.3 (not concave)
Iteration 218: log likelihood = -661762.8 (not concave)
Iteration 219: log likelihood = -657346.22 (not concave)
Iteration 220: log likelihood = -653020.62 (not concave)
Iteration 221: log likelihood = -648726.7 (not concave)
--Break--
r(1);
. *The point is that this likelihood maximization procedure was not maximizing very efficiently
. desmat: poisson count meth*mgen*fgen*year feth*fgen*mgen*year ethintct*mgen*fgen, verbose difficult
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.fgen ind(1).ind(1)
17 _x_53 _x_55 feth.mgen ind(1).ind(1)
18 _x_56 feth.fgen.mgen ind(1).ind(1).ind(1)
19 _x_57 _x_64 feth.year ind(1).ind(70)
20 _x_65 _x_71 feth.fgen.year ind(1).ind(1).ind(70)
21 _x_72 _x_76 feth.mgen.year ind(1).ind(1).ind(70)
22 _x_77 _x_80 feth.fgen.mgen.year ind(1).ind(1).ind(1).ind(70)
23 _x_81 _x_85 ethintct ind(0)
24 _x_86 _x_87 ethintct.mgen ind(0).ind(1)
25 _x_88 _x_92 ethintct.fgen ind(0).ind(1)
26 _x_93 _x_95 ethintct.mgen.fgen ind(0).ind(1).ind(1)
Iteration 0: log likelihood = -11376909 (not concave)
Iteration 1: log likelihood = -6217984.2 (not concave)
Iteration 2: log likelihood = -3846571.7 (not concave)
Iteration 3: log likelihood = -2578151.8 (not concave)
Iteration 4: log likelihood = -2028946.4 (not concave)
Iteration 5: log likelihood = -887726.07 (not concave)
Iteration 6: log likelihood = -728918 (not concave)
Iteration 7: log likelihood = -596613.06
Iteration 8: log likelihood = -578958.68 (backed up)
Iteration 9: log likelihood = -472109.71
Iteration 10: log likelihood = -241883.83
Iteration 11: log likelihood = -31214.76
Iteration 12: log likelihood = -6442.2843
Iteration 13: log likelihood = -2209.7905
Iteration 14: log likelihood = -1774.1755
Iteration 15: log likelihood = -1759.6223
Iteration 16: log likelihood = -1759.6216
Iteration 17: log likelihood = -1759.6216
Poisson regression Number of obs = 225
LR chi2(95) = 4501708.05
Prob > chi2 = 0.0000
Log likelihood = -1759.6216 Pseudo R2 = 0.9992
------------------------------------------------------------------------------
count | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_x_1 | 1.165103 .4197851 2.78 0.006 .3423393 1.987867
_x_2 | 1.099724 .4270947 2.57 0.010 .2626342 1.936815
_x_3 | 1.732219 .3346601 5.18 0.000 1.076298 2.388141
_x_4 | 2.78117 .3811889 7.30 0.000 2.034053 3.528286
_x_5 | 2.938448 .218047 13.48 0.000 2.511084 3.365812
_x_6 | -1.265604 .3251113 -3.89 0.000 -1.90281 -.6283978
_x_7 | -1.356819 .3193536 -4.25 0.000 -1.982741 -.7308977
_x_8 | -2.21903 .4621251 -4.80 0.000 -3.124778 -1.313282
_x_9 | .3484247 .309082 1.13 0.260 -.2573648 .9542142
_x_10 | 3.391698 .2958364 11.46 0.000 2.811869 3.971527
_x_11 | .9930531 .2750947 3.61 0.000 .4538773 1.532229
_x_12 | 1.408697 .2920315 4.82 0.000 .8363259 1.981068
_x_13 | .3109707 .2320988 1.34 0.180 -.1439346 .7658759
_x_14 | .8970384 .328657 2.73 0.006 .2528825 1.541194
_x_15 | 3.337071 .2764124 12.07 0.000 2.795312 3.878829
_x_16 | 2.541448 .193653 13.12 0.000 2.161895 2.921001
_x_17 | .0057851 .3220871 0.02 0.986 -.625494 .6370642
_x_18 | -.1376674 .273006 -0.50 0.614 -.6727493 .3974145
_x_19 | .2382366 .3163083 0.75 0.451 -.3817162 .8581895
_x_20 | .8098165 .4373606 1.85 0.064 -.0473945 1.667027
_x_21 | .1993681 .3404007 0.59 0.558 -.4678049 .8665412
_x_22 | -.0913696 .480959 -0.19 0.849 -1.034032 .8512926
_x_23 | -.5945171 .2301859 -2.58 0.010 -1.045673 -.1433609
_x_24 | .5452777 .3385195 1.61 0.107 -.1182083 1.208764
_x_25 | -.2315737 .4206013 -0.55 0.582 -1.055937 .5927897
_x_26 | -.7468544 .4282323 -1.74 0.081 -1.586174 .0924654
_x_27 | -.8127895 .3269364 -2.49 0.013 -1.453573 -.1720058
_x_28 | -.8967258 .4711462 -1.90 0.057 -1.820155 .0267039
_x_29 | -.1162308 .3524714 -0.33 0.742 -.807062 .5746005
_x_30 | -.8566941 .2271323 -3.77 0.000 -1.301865 -.4115229
_x_31 | -.6535567 .3369687 -1.94 0.052 -1.314003 .0068898
_x_32 | .2434381 .4231505 0.58 0.565 -.5859217 1.072798
_x_33 | -.7671242 .3004113 -2.55 0.011 -1.35592 -.1783288
_x_34 | .2762054 .3384574 0.82 0.414 -.3871589 .9395697
_x_35 | -.5968301 .3033839 -1.97 0.049 -1.191452 -.0022086
_x_36 | -.2784866 .3820579 -0.73 0.466 -1.027306 .4703331
_x_37 | -.9931224 .1933954 -5.14 0.000 -1.37217 -.6140743
_x_38 | -2.097025 .2781947 -7.54 0.000 -2.642277 -1.551774
_x_39 | .2315129 .2805798 0.83 0.409 -.3184134 .7814392
_x_40 | -.0848601 .3324044 -0.26 0.798 -.7363606 .5666405
_x_41 | -.3748647 .2978854 -1.26 0.208 -.9587094 .20898
_x_42 | .6197767 .3363676 1.84 0.065 -.0394917 1.279045
_x_43 | 1.056824 .3842093 2.75 0.006 .3037872 1.80986
_x_44 | .498711 .3119521 1.60 0.110 -.1127038 1.110126
_x_45 | 2.611911 .4771577 5.47 0.000 1.6767 3.547123
_x_46 | 2.650934 .4757676 5.57 0.000 1.718446 3.583421
_x_47 | 3.641932 .3422167 10.64 0.000 2.9712 4.312665
_x_48 | 3.961282 .4450352 8.90 0.000 3.089029 4.833535
_x_49 | -1.661012 .3626822 -4.58 0.000 -2.371856 -.9501681
_x_50 | -1.754534 .3557518 -4.93 0.000 -2.451795 -1.057273
_x_51 | -3.214011 .4958969 -6.48 0.000 -4.185951 -2.24207
_x_52 | -.7426408 .343427 -2.16 0.031 -1.415745 -.0695363
_x_53 | .1459694 .3188156 0.46 0.647 -.4788977 .7708365
_x_54 | .5333194 .3239435 1.65 0.100 -.1015981 1.168237
_x_55 | .540312 .2906437 1.86 0.063 -.0293391 1.109963
_x_56 | .3062494 .3680651 0.83 0.405 -.4151449 1.027644
_x_57 | -.6306041 .3523038 -1.79 0.073 -1.321107 .0598987
_x_58 | -1.272673 .4824537 -2.64 0.008 -2.218265 -.3270812
_x_59 | -.1958369 .477182 -0.41 0.682 -1.131096 .7394227
_x_60 | -.1173356 .3463781 -0.34 0.735 -.7962242 .561553
_x_61 | -.9286045 .5067844 -1.83 0.067 -1.921884 .0646748
_x_62 | -1.408424 .5102802 -2.76 0.006 -2.408555 -.4082931
_x_63 | -.9202012 .3288759 -2.80 0.005 -1.564786 -.2756163
_x_64 | -.0833885 .2915921 -0.29 0.775 -.6548986 .4881215
_x_65 | .8884304 .4736093 1.88 0.061 -.0398267 1.816688
_x_66 | 1.636779 .3625487 4.51 0.000 .9261966 2.347361
_x_67 | -.0578633 .3521096 -0.16 0.869 -.7479854 .6322589
_x_68 | .2180689 .4741212 0.46 0.646 -.7111916 1.147329
_x_69 | .7182096 .34775 2.07 0.039 .0366321 1.399787
_x_70 | 1.319471 .3505478 3.76 0.000 .6324099 2.006532
_x_71 | .7037721 .4381724 1.61 0.108 -.1550299 1.562574
_x_72 | .797247 .3277339 2.43 0.015 .1549003 1.439594
_x_73 | .1484815 .3304075 0.45 0.653 -.4991053 .7960683
_x_74 | .8969982 .3780301 2.37 0.018 .1560729 1.637923
_x_75 | 1.212366 .3807276 3.18 0.001 .4661532 1.958578
_x_76 | -1.195117 .4412544 -2.71 0.007 -2.059959 -.3302739
_x_77 | .4666456 .3253562 1.43 0.151 -.1710409 1.104332
_x_78 | .2202746 .3327456 0.66 0.508 -.4318947 .8724439
_x_79 | .5723164 .2964314 1.93 0.054 -.0086786 1.153311
_x_80 | 1.922575 .3377677 5.69 0.000 1.260563 2.584588
_x_81 | 4.605593 .1326462 34.72 0.000 4.345612 4.865575
_x_82 | 3.668658 .0967116 37.93 0.000 3.479107 3.858209
_x_83 | 1.668493 .1117252 14.93 0.000 1.449516 1.88747
_x_84 | 1.43289 .1061399 13.50 0.000 1.22486 1.64092
_x_85 | 1.545125 .0596784 25.89 0.000 1.428158 1.662093
_x_86 | .1886668 .0651996 2.89 0.004 .0608779 .3164558
_x_87 | .7919784 .0792434 9.99 0.000 .6366641 .9472927
_x_88 | .3685655 .1766968 2.09 0.037 .0222461 .7148849
_x_89 | -.6291632 .0767838 -8.19 0.000 -.7796567 -.4786697
_x_90 | .4232148 .0857049 4.94 0.000 .2552363 .5911933
_x_91 | .3565253 .1440862 2.47 0.013 .0741215 .6389291
_x_92 | .5302306 .0859417 6.17 0.000 .361788 .6986731
_x_93 | 2.242294 .1246851 17.98 0.000 1.997916 2.486672
_x_94 | .8571449 .1034412 8.29 0.000 .654404 1.059886
_x_95 | .4182267 .0665366 6.29 0.000 .2878174 .548636
_cons | -5.129297 .3646622 -14.07 0.000 -5.844022 -4.414572
------------------------------------------------------------------------------
------------------------------------------------------------------------------------------
Poisson regression
------------------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -1759.622
LR chi square: 4501708.052
Model degrees of freedom: 95
Pseudo R-squared: 0.999
Prob: 0.000
------------------------------------------------------------------------------------------
nr Effect Coeff s.e.
------------------------------------------------------------------------------------------
count
meth
1 Mex_Am 1.165** 0.420
2 Oth_H 1.100* 0.427
3 Oth_NH 1.732** 0.335
4 Wht_NH 2.781** 0.381
mgen
5 US native 2.938** 0.218
meth.mgen
6 Mex_Am.US native -1.266** 0.325
7 Oth_H.US native -1.357** 0.319
8 Oth_NH.US native -2.219** 0.462
9 Wht_NH.US native 0.348 0.309
fgen
10 US native 3.392** 0.296
meth.fgen
11 Mex_Am.US native 0.993** 0.275
12 Oth_H.US native 1.409** 0.292
13 Wht_NH.US native 0.311 0.232
meth.mgen.fgen
14 Oth_NH.US native.US native 0.897** 0.329
year
15 80 3.337** 0.276
16 90 2.541** 0.194
meth.year
17 Mex_Am.80 0.006 0.322
18 Mex_Am.90 -0.138 0.273
19 Oth_H.80 0.238 0.316
20 Oth_H.90 0.810 0.437
21 Oth_NH.80 0.199 0.340
22 Oth_NH.90 -0.091 0.481
23 Wht_NH.90 -0.595** 0.230
mgen.year
24 US native.90 0.545 0.339
meth.mgen.year
25 Mex_Am.US native.80 -0.232 0.421
26 Oth_H.US native.80 -0.747 0.428
27 Oth_H.US native.90 -0.813* 0.327
28 Oth_NH.US native.80 -0.897 0.471
29 Oth_NH.US native.90 -0.116 0.352
30 Wht_NH.US native.80 -0.857** 0.227
fgen.year
31 US native.80 -0.654 0.337
meth.fgen.year
32 Mex_Am.US native.90 0.243 0.423
33 Oth_H.US native.90 -0.767* 0.300
34 Oth_NH.US native.90 0.276 0.338
35 Wht_NH.US native.80 -0.597* 0.303
36 Wht_NH.US native.90 -0.278 0.382
mgen.fgen.year
37 US native.US native.80 -0.993** 0.193
38 US native.US native.90 -2.097** 0.278
meth.mgen.fgen.year
39 Mex_Am.US native.US native.80 0.232 0.281
40 Mex_Am.US native.US native.90 -0.085 0.332
41 Oth_H.US native.US native.80 -0.375 0.298
42 Oth_NH.US native.US native.80 0.620 0.336
43 Wht_NH.US native.US native.80 1.057** 0.384
44 Wht_NH.US native.US native.90 0.499 0.312
feth
45 Mex_Am 2.612** 0.477
46 Oth_H 2.651** 0.476
47 Oth_NH 3.642** 0.342
48 Wht_NH 3.961** 0.445
feth.fgen
49 Mex_Am.US native -1.661** 0.363
50 Oth_H.US native -1.755** 0.356
51 Oth_NH.US native -3.214** 0.496
52 Wht_NH.US native -0.743* 0.343
feth.mgen
53 Mex_Am.US native 0.146 0.319
54 Oth_H.US native 0.533 0.324
55 Wht_NH.US native 0.540 0.291
feth.fgen.mgen
56 Oth_NH.US native.US native 0.306 0.368
feth.year
57 Mex_Am.80 -0.631 0.352
58 Mex_Am.90 -1.273** 0.482
59 Oth_H.80 -0.196 0.477
60 Oth_H.90 -0.117 0.346
61 Oth_NH.80 -0.929 0.507
62 Oth_NH.90 -1.408** 0.510
63 Wht_NH.80 -0.920** 0.329
64 Wht_NH.90 -0.083 0.292
feth.fgen.year
65 Mex_Am.US native.80 0.888 0.474
66 Mex_Am.US native.90 1.637** 0.363
67 Oth_H.US native.80 -0.058 0.352
68 Oth_H.US native.90 0.218 0.474
69 Oth_NH.US native.80 0.718* 0.348
70 Oth_NH.US native.90 1.319** 0.351
71 Wht_NH.US native.80 0.704 0.438
feth.mgen.year
72 Mex_Am.US native.90 0.797* 0.328
73 Oth_H.US native.80 0.148 0.330
74 Oth_NH.US native.80 0.897* 0.378
75 Oth_NH.US native.90 1.212** 0.381
76 Wht_NH.US native.90 -1.195** 0.441
feth.fgen.mgen.year
77 Mex_Am.US native.US native.80 0.467 0.325
78 Oth_H.US native.US native.90 0.220 0.333
79 Wht_NH.US native.US native.80 0.572 0.296
80 Wht_NH.US native.US native.90 1.923** 0.338
ethintct
81 1 4.606** 0.133
82 2 3.669** 0.097
83 3 1.668** 0.112
84 4 1.433** 0.106
85 5 1.545** 0.060
ethintct.mgen
86 2.US native 0.189** 0.065
87 3.US native 0.792** 0.079
ethintct.fgen
88 1.US native 0.369* 0.177
89 2.US native -0.629** 0.077
90 3.US native 0.423** 0.086
91 4.US native 0.357* 0.144
92 5.US native 0.530** 0.086
ethintct.mgen.fgen
93 1.US native.US native 2.242** 0.125
94 4.US native.US native 0.857** 0.103
95 5.US native.US native 0.418** 0.067
96 _cons -5.129** 0.365
------------------------------------------------------------------------------------------
* p < .05
** p < .01
. *So with difficult, the same model took 17 steps to converge, converged in 5 seconds on the professor's old laptop, and note that the SEs are all perfectly reasonable. The key point here is that one maximization algorithm can work very well while another does not work at all with the same data and the same model. The practical lesson is that with Poisson and Stata, the difficult option is very often useful.
. exit, clear