(Note: related to a previous thread, but it was probably confusing: https://www.statalist.org/forums/for...group-analysis
Code:
MODEL . mlogit gender_n c.year##position_department_n, rrr vce(cluster person) Iteration 0: log pseudolikelihood = -34931.124 Iteration 1: log pseudolikelihood = -34522.775 Iteration 2: log pseudolikelihood = -34505.94 Iteration 3: log pseudolikelihood = -34505.897 Iteration 4: log pseudolikelihood = -34505.897 Multinomial logistic regression Number of obs = 42,217 Wald chi2(30) = 473.31 Prob > chi2 = 0.0000 Log pseudolikelihood = -34505.897 Pseudo R2 = 0.0122 (Std. Err. adjusted for 16,011 clusters in person) ---------------------------------------------------------------------------------------------- | Robust gender_n | RRR Std. Err. z P>|z| [95% Conf. Interval] -----------------------------+---------------------------------------------------------------- F | (base outcome) -----------------------------+---------------------------------------------------------------- M | year | 1.087405 .0201943 4.51 0.000 1.048537 1.127714 | position_department_n | Principal, Marketing | 4.74e+65 2.93e+67 2.45 0.014 1.49e+13 1.5e+118 Principal, R&D | 3.58e+21 4.33e+23 0.41 0.681 5.50e-82 2.3e+124 Principal, Social Sci | 5.72e+39 2.49e+41 2.10 0.035 517.6844 6.32e+76 Senior, HR | 4.61e-42 4.90e-40 -0.90 0.370 1.6e-132 1.29e+49 Senior, Marketing | 5.08e+40 2.42e+42 1.96 0.050 1.147795 2.25e+81 Senior, R&D | 5.00e+23 2.36e+25 1.16 0.248 3.11e-17 8.07e+63 Senior, Social Sci | 5.10e+10 2.64e+12 0.48 0.634 4.56e-34 5.71e+54 | position_department_n#c.year | Principal, Marketing | .9275847 .028468 -2.45 0.014 .8734334 .9850933 Principal, R&D | .975824 .058644 -0.41 0.684 .867395 1.097807 Principal, Social Sci | .9555847 .0206889 -2.10 0.036 .9158835 .9970069 Senior, HR | 1.048612 .0554319 0.90 0.369 .9454057 1.163084 Senior, Marketing | .9546213 .0226777 -1.95 0.051 .9111926 1.00012 Senior, R&D | .9732994 .0228722 -1.15 0.249 .9294874 1.019176 Senior, Social Sci | .9877963 .0254299 -0.48 0.633 .9391913 1.038917 | _cons | 1.88e-74 7.01e-73 -4.55 0.000 3.2e-106 1.11e-42 -----------------------------+---------------------------------------------------------------- U | year | .7736713 .025425 -7.81 0.000 .7254101 .8251432 | position_department_n | Principal, Marketing | 5.3e-206 4.4e-204 -5.63 0.000 2.0e-277 1.4e-134 Principal, R&D | 2.4e-229 3.7e-227 -3.52 0.000 0 7.0e-102 Principal, Social Sci | 1.60e+65 1.27e+67 1.90 0.058 .007974 3.2e+132 Senior, HR | 6.1e-121 8.8e-119 -1.93 0.053 8.2e-243 45.42893 Senior, Marketing | 2.4e-167 1.8e-165 -5.08 0.000 1.2e-231 5.0e-103 Senior, R&D | 1.7e-125 1.3e-123 -3.68 0.000 5.2e-192 5.41e-59 Senior, Social Sci | 1.2e-131 9.2e-130 -3.83 0.000 1.4e-198 1.00e-64 | position_department_n#c.year | Principal, Marketing | 1.26561 .0528597 5.64 0.000 1.166134 1.373571 Principal, R&D | 1.299867 .0968639 3.52 0.000 1.12323 1.504281 Principal, Social Sci | .928099 .0365388 -1.90 0.058 .8591775 1.002549 Senior, HR | 1.147918 .081795 1.94 0.053 .9982941 1.319968 Senior, Marketing | 1.210673 .0455427 5.08 0.000 1.124622 1.303308 Senior, R&D | 1.153848 .0448898 3.68 0.000 1.069136 1.245271 Senior, Social Sci | 1.162135 .0454958 3.84 0.000 1.0763 1.254815 | _cons | 9.7e+222 6.4e+224 7.78 0.000 6.4e+166 1.5e+279 ---------------------------------------------------------------------------------------------- Note: _cons estimates baseline relative risk for each outcome. . CERTAIN MARGINS NOT ESTIMABLE . margins i.position_department_n, at(year=(2007(1)2013)) Adjusted predictions Number of obs = 42,217 Model VCE : Robust 1._predict : Pr(gender_n==F), predict(pr outcome(4)) 2._predict : Pr(gender_n==M), predict(pr outcome(5)) 3._predict : Pr(gender_n==U), predict(pr outcome(6)) 1._at : year = 2007 2._at : year = 2008 3._at : year = 2009 4._at : year = 2010 5._at : year = 2011 6._at : year = 2012 7._at : year = 2013 ---------------------------------------------------------------------------------------------------- | Delta-method | Margin Std. Err. z P>|z| [95% Conf. Interval] -----------------------------------+---------------------------------------------------------------- _predict#_at#position_department_n | 1#1#Principal, HR | . (not estimable) 1#1#Principal, Marketing | .6583075 .0202208 32.56 0.000 .6186753 .6979396 1#1#Principal, R&D | . (not estimable) 1#1#Principal, Social Sci | .6250972 .0089476 69.86 0.000 .6075602 .6426342 1#1#Senior, HR | .6922345 .0329192 21.03 0.000 .627714 .756755 1#1#Senior, Marketing | .6404988 .0139097 46.05 0.000 .6132362 .6677613 1#1#Senior, R&D | .6891176 .011805 58.38 0.000 .6659802 .712255 1#1#Senior, Social Sci | .6970804 .0150392 46.35 0.000 .667604 .7265568 1#2#Principal, HR | . (not estimable) 1#2#Principal, Marketing | .6592583 .0181735 36.28 0.000 .6236388 .6948777 1#2#Principal, R&D | . (not estimable) 1#2#Principal, Social Sci | .6556696 .0072335 90.64 0.000 .6414923 .669847 1#2#Senior, HR | .6891251 .0261109 26.39 0.000 .6379487 .7403016 1#2#Senior, Marketing | .6407317 .0123407 51.92 0.000 .6165445 .664919 1#2#Senior, R&D | .6913654 .0102943 67.16 0.000 .6711889 .7115418 1#2#Senior, Social Sci | .7007748 .0135274 51.80 0.000 .6742616 .7272881 1#3#Principal, HR | . (not estimable) 1#3#Principal, Marketing | .6601594 .0171215 38.56 0.000 .6266018 .693717 1#3#Principal, R&D | . (not estimable) 1#3#Principal, Social Sci | .6778312 .0065145 104.05 0.000 .665063 .6905995 1#3#Senior, HR | .682689 .0213363 32.00 0.000 .6408707 .7245072 1#3#Senior, Marketing | .6404036 .0113035 56.66 0.000 .6182491 .662558 1#3#Senior, R&D | .6921605 .0093729 73.85 0.000 .6737899 .7105311 1#3#Senior, Social Sci | .7027991 .0127094 55.30 0.000 .6778891 .7277092 1#4#Principal, HR | . (not estimable) 1#4#Principal, Marketing | .6610112 .0172398 38.34 0.000 .6272217 .6948006 1#4#Principal, R&D | . (not estimable) 1#4#Principal, Social Sci | .6928427 .0064118 108.06 0.000 .6802758 .7054096 1#4#Senior, HR | .6729726 .0196286 34.29 0.000 .6345011 .711444 1#4#Senior, Marketing | .6395307 .0109476 58.42 0.000 .6180738 .6609877 1#4#Senior, R&D | .6915785 .0091341 75.71 0.000 .673676 .709481 1#4#Senior, Social Sci | .7031978 .0126017 55.80 0.000 .6784988 .7278967 1#5#Principal, HR | . (not estimable) 1#5#Principal, Marketing | .6618141 .018501 35.77 0.000 .6255528 .6980753 1#5#Principal, R&D | . (not estimable) 1#5#Principal, Social Sci | .7020658 .0067912 103.38 0.000 .6887552 .7153763 1#5#Senior, HR | .6600712 .0220509 29.93 0.000 .6168522 .7032901 1#5#Senior, Marketing | .6381306 .0113535 56.21 0.000 .6158782 .6603829 1#5#Senior, R&D | .6896983 .0096197 71.70 0.000 .670844 .7085526 1#5#Senior, Social Sci | .7020239 .0131906 53.22 0.000 .6761709 .7278769 1#6#Principal, HR | . (not estimable) 1#6#Principal, Marketing | .6625685 .0206949 32.02 0.000 .6220072 .7031298 1#6#Principal, R&D | . (not estimable) 1#6#Principal, Social Sci | .7067637 .0076539 92.34 0.000 .6917623 .7217651 1#6#Senior, HR | .6441298 .0282649 22.79 0.000 .5887315 .699528 1#6#Senior, Marketing | .6362212 .0124761 51.00 0.000 .6117685 .660674 1#6#Senior, R&D | .6866003 .0107752 63.72 0.000 .6654813 .7077193 1#6#Senior, Social Sci | .6993378 .0144285 48.47 0.000 .6710584 .7276173 1#7#Principal, HR | . (not estimable) 1#7#Principal, Marketing | .6632749 .0235625 28.15 0.000 .6170932 .7094566 1#7#Principal, R&D | . (not estimable) 1#7#Principal, Social Sci | .7080094 .008972 78.91 0.000 .6904245 .7255942 1#7#Senior, HR | .6253429 .0371503 16.83 0.000 .5525298 .6981561 1#7#Senior, Marketing | .6338215 .0141828 44.69 0.000 .6060237 .6616192 1#7#Senior, R&D | .682365 .0124851 54.65 0.000 .6578947 .7068353 1#7#Senior, Social Sci | .6952055 .0162499 42.78 0.000 .6633564 .7270547 2#1#Principal, HR | . (not estimable) 2#1#Principal, Marketing | .1924652 .0167435 11.49 0.000 .1596486 .2252818 2#1#Principal, R&D | . (not estimable) 2#1#Principal, Social Sci | .1840082 .0071937 25.58 0.000 .1699089 .1981075 2#1#Senior, HR | .1544592 .0245907 6.28 0.000 .1062624 .2026561 2#1#Senior, Marketing | .2209743 .0119726 18.46 0.000 .1975086 .2444401 2#1#Senior, R&D | .1817257 .0095304 19.07 0.000 .1630465 .2004049 2#1#Senior, Social Sci | .1444917 .0112957 12.79 0.000 .1223525 .1666309 2#2#Principal, HR | . (not estimable) 2#2#Principal, Marketing | .1944124 .0150486 12.92 0.000 .1649176 .2239072 2#2#Principal, R&D | . (not estimable) 2#2#Principal, Social Sci | .2005558 .0065126 30.79 0.000 .1877913 .2133204 2#2#Senior, HR | .1753334 .0213475 8.21 0.000 .1334932 .2171737 2#2#Senior, Marketing | .2294681 .0107672 21.31 0.000 .2083647 .2505714 2#2#Senior, R&D | .1929605 .0085814 22.49 0.000 .1761413 .2097797 2#2#Senior, Social Sci | .1560261 .0107474 14.52 0.000 .1349615 .1770907 2#3#Principal, HR | . (not estimable) 2#3#Principal, Marketing | .1963641 .0141295 13.90 0.000 .1686707 .2240575 2#3#Principal, R&D | . (not estimable) 2#3#Principal, Social Sci | .215443 .0060046 35.88 0.000 .2036742 .2272118 2#3#Senior, HR | .1980594 .0183081 10.82 0.000 .1621763 .2339426 2#3#Senior, Marketing | .2380796 .0099376 23.96 0.000 .2186022 .257557 2#3#Senior, R&D | .2044586 .0079183 25.82 0.000 .188939 .2199783 2#3#Senior, Social Sci | .1680772 .0104484 16.09 0.000 .1475987 .1885558 2#4#Principal, HR | . (not estimable) 2#4#Principal, Marketing | .1983202 .0141847 13.98 0.000 .1705187 .2261218 2#4#Principal, R&D | . (not estimable) 2#4#Principal, Social Sci | .2288264 .0058645 39.02 0.000 .2173321 .2403207 2#4#Senior, HR | .2226261 .0172002 12.94 0.000 .1889142 .2563379 2#4#Senior, Marketing | .2468041 .0096882 25.47 0.000 .2278155 .2657927 2#4#Senior, R&D | .2162111 .0077747 27.81 0.000 .2009729 .2314493 2#4#Senior, Social Sci | .18064 .0105847 17.07 0.000 .1598943 .2013857 2#5#Principal, HR | . (not estimable) 2#5#Principal, Marketing | .2002807 .0152473 13.14 0.000 .1703965 .230165 2#5#Principal, R&D | . (not estimable) 2#5#Principal, Social Sci | .2409405 .0062712 38.42 0.000 .2286491 .2532319 2#5#Senior, HR | .2489863 .0201027 12.39 0.000 .2095858 .2883868 2#5#Senior, Marketing | .2556366 .0101662 25.15 0.000 .2357112 .2755619 2#5#Senior, R&D | .2282094 .0083375 27.37 0.000 .2118682 .2445505 2#5#Senior, Social Sci | .1937078 .0113197 17.11 0.000 .1715216 .215894 2#6#Principal, HR | . (not estimable) 2#6#Principal, Marketing | .2022455 .01717 11.78 0.000 .1685929 .2358982 2#6#Principal, R&D | . (not estimable) 2#6#Principal, Social Sci | .2520384 .0072581 34.72 0.000 .2378128 .2662641 2#6#Senior, HR | .2770538 .027118 10.22 0.000 .2239034 .3302042 2#6#Senior, Marketing | .2645721 .0113736 23.26 0.000 .2422803 .2868639 2#6#Senior, R&D | .2404452 .0096269 24.98 0.000 .2215768 .2593136 2#6#Senior, Social Sci | .2072722 .0127283 16.28 0.000 .1823252 .2322191 2#7#Principal, HR | . (not estimable) 2#7#Principal, Marketing | .2042145 .019737 10.35 0.000 .1655307 .2428984 2#7#Principal, R&D | . (not estimable) 2#7#Principal, Social Sci | .2623567 .0087208 30.08 0.000 .2452643 .2794491 2#7#Senior, HR | .3067008 .0369607 8.30 0.000 .2342592 .3791425 2#7#Senior, Marketing | .2736058 .0131917 20.74 0.000 .2477506 .2994611 2#7#Senior, R&D | .2529104 .011524 21.95 0.000 .2303238 .2754969 2#7#Senior, Social Sci | .2213227 .0147861 14.97 0.000 .1923425 .250303 3#1#Principal, HR | . (not estimable) 3#1#Principal, Marketing | .1492273 .0149122 10.01 0.000 .1199999 .1784548 3#1#Principal, R&D | . (not estimable) 3#1#Principal, Social Sci | .1908946 .0070506 27.07 0.000 .1770757 .2047136 3#1#Senior, HR | .1533063 .0269603 5.69 0.000 .100465 .2061475 3#1#Senior, Marketing | .1385269 .0101728 13.62 0.000 .1185885 .1584653 3#1#Senior, R&D | .1291567 .0089419 14.44 0.000 .111631 .1466824 3#1#Senior, Social Sci | .1584279 .0119919 13.21 0.000 .1349242 .1819315 3#2#Principal, HR | . (not estimable) 3#2#Principal, Marketing | .1463293 .0135234 10.82 0.000 .119824 .1728347 3#2#Principal, R&D | . (not estimable) 3#2#Principal, Social Sci | .1437746 .0041703 34.48 0.000 .135601 .1519481 3#2#Senior, HR | .1355414 .019277 7.03 0.000 .0977592 .1733236 3#2#Senior, Marketing | .1298002 .0088667 14.64 0.000 .1124218 .1471786 3#2#Senior, R&D | .1156741 .0073956 15.64 0.000 .101179 .1301693 3#2#Senior, Social Sci | .143199 .0102279 14.00 0.000 .1231528 .1632453 3#3#Principal, HR | . (not estimable) 3#3#Principal, Marketing | .1434765 .0129078 11.12 0.000 .1181776 .1687755 3#3#Principal, R&D | . (not estimable) 3#3#Principal, Social Sci | .1067258 .0033748 31.62 0.000 .1001113 .1133402 3#3#Senior, HR | .1192516 .0144499 8.25 0.000 .0909303 .147573 3#3#Senior, Marketing | .1215168 .008054 15.09 0.000 .1057313 .1373023 3#3#Senior, R&D | .1033809 .0065696 15.74 0.000 .0905047 .1162571 3#3#Senior, Social Sci | .1291236 .0092939 13.89 0.000 .110908 .1473393 3#4#Principal, HR | . (not estimable) 3#4#Principal, Marketing | .1406686 .0130936 10.74 0.000 .1150055 .1663317 3#4#Principal, R&D | . (not estimable) 3#4#Principal, Social Sci | .0783309 .003537 22.15 0.000 .0713986 .0852633 3#4#Senior, HR | .1044014 .0127908 8.16 0.000 .0793318 .1294709 3#4#Senior, Marketing | .1136652 .0077097 14.74 0.000 .0985544 .1287759 3#4#Senior, R&D | .0922104 .0063246 14.58 0.000 .0798145 .1046063 3#4#Senior, Social Sci | .1161622 .0090283 12.87 0.000 .0984671 .1338574 3#5#Principal, HR | . (not estimable) 3#5#Principal, Marketing | .1379052 .0139769 9.87 0.000 .1105109 .1652995 3#5#Principal, R&D | . (not estimable) 3#5#Principal, Social Sci | .0569937 .0036408 15.65 0.000 .0498579 .0641296 3#5#Senior, HR | .0909425 .013445 6.76 0.000 .0645908 .1172942 3#5#Senior, Marketing | .1062329 .0077454 13.72 0.000 .0910522 .1214135 3#5#Senior, R&D | .0820923 .0064307 12.77 0.000 .0694883 .0946963 3#5#Senior, Social Sci | .1042683 .0091769 11.36 0.000 .0862819 .1222547 3#6#Principal, HR | . (not estimable) 3#6#Principal, Marketing | .135186 .0153761 8.79 0.000 .1050493 .1653226 3#6#Principal, R&D | . (not estimable) 3#6#Principal, Social Sci | .0411978 .003493 11.79 0.000 .0343518 .0480439 3#6#Senior, HR | .0788165 .0149149 5.28 0.000 .0495839 .1080491 3#6#Senior, Marketing | .0992067 .0080364 12.34 0.000 .0834556 .1149577 3#6#Senior, R&D | .0729545 .0066772 10.93 0.000 .0598674 .0860416 3#6#Senior, Social Sci | .09339 .0095025 9.83 0.000 .0747654 .1120146 3#7#Principal, HR | . (not estimable) 3#7#Principal, Marketing | .1325106 .0171124 7.74 0.000 .0989709 .1660503 3#7#Principal, R&D | . (not estimable) 3#7#Principal, Social Sci | .029634 .0031621 9.37 0.000 .0234363 .0358316 3#7#Senior, HR | .0679562 .0162829 4.17 0.000 .0360424 .0998701 3#7#Senior, Marketing | .0925727 .008465 10.94 0.000 .0759816 .1091638 3#7#Senior, R&D | .0647247 .0069292 9.34 0.000 .0511438 .0783056 3#7#Senior, Social Sci | .0834717 .0098446 8.48 0.000 .0641767 .1027668 ----------------------------------------------------------------------------------------------------
0 Response to margins after mlogit not estimable - why?
Post a Comment