让我们说我想在R中使用在线数据集做一个简单的多项logit模型：
library(nnet)
data <- data.table(read.dta('http://data.princeton.edu/wws509/datasets/irished.dta'))
ml <- multinom(educg ~ gender + prestigeg + reasong, data=data)
summary(ml)
您获得以下输出
摘要（毫升） 呼叫： multinom（公式= educg~sexx + prestigeg + reasong，data = data）
Coefficients:
(Intercept) genderfemale prestigegQ2 prestigegQ3 prestigegQ4 reasongQ2 reasongQ3 reasongQ4
senior -1.650999 0.3051297 0.8704957 1.189714 1.340206 -0.08303942 1.035163 1.627145
3rd level -5.792979 0.1615402 1.5331076 1.682500 2.227006 2.11053104 3.232968 4.963707
Std. Errors:
(Intercept) genderfemale prestigegQ2 prestigegQ3 prestigegQ4 reasongQ2 reasongQ3 reasongQ4
senior 0.3203241 0.2304163 0.3023462 0.3376034 0.3288158 0.2990188 0.3063954 0.3488479
3rd level 1.1165939 0.3477700 0.5534933 0.5878517 0.5433370 1.0789145 1.0644124 1.0532858
Residual Deviance: 730.8832
AIC: 762.8832
如果我在Stata中执行类似的例程：
use http://data.princeton.edu/wws509/datasets/irished.dta
mlogit educg gender prestigeg reasong
我得到以下输出：
Iteration 0: log likelihood = -433.16499
Iteration 1: log likelihood = -376.86517
Iteration 2: log likelihood = -371.52279
Iteration 3: log likelihood = -371.42355
Iteration 4: log likelihood = -371.42343
Iteration 5: log likelihood = -371.42343
Multinomial logistic regression Number of obs = 435
LR chi2(6) = 123.48
Prob > chi2 = 0.0000
Log likelihood = -371.42343 Pseudo R2 = 0.1425
------------------------------------------------------------------------------
educg | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
junior | (base outcome)
-------------+----------------------------------------------------------------
senior |
gender | .2577712 .2247087 1.15 0.251 -.1826498 .6981921
prestigeg | .4394042 .1027884 4.27 0.000 .2379427 .6408657
reasong | .5584275 .1059711 5.27 0.000 .3507279 .766127
_cons | -2.890597 .533933 -5.41 0.000 -3.937086 -1.844108
-------------+----------------------------------------------------------------
3rd_level |
gender | .1360704 .3416126 0.40 0.690 -.5334779 .8056188
prestigeg | .6387618 .1532933 4.17 0.000 .3383125 .9392111
reasong | 1.431763 .197151 7.26 0.000 1.045355 1.818172
_cons | -7.032375 .9904472 -7.10 0.000 -8.973616 -5.091134
------------------------------------------------------------------------------
为什么这些值完全不同？如何在R？
中为多项logit模型获得类似Stata的输出