Hello, everyone! I have encountered unestimable margins when running a logistic regression with an interaction.
Here is my output.
After reading manuals and researching on this topic, it seems that it is likely caused by empty cells. However, I am using a large dataset and there is no empty cell when I run the crosstab.
When I add noestimcheck, the results show up and they look reasonable. Should I trust the results? I found out this old post http://statalist.1588530.n2.nabble.c...td3407157.html and it seems that noestimcheck needs to be used with great caution with interaction terms. I am using Stata 16.
Thanks!
Here is my output.
Code:
. logit homeown i.raceth##i.forborn $dems $ses yrsusa i.linguiso $other if both==1, nocons
Iteration 0: log likelihood = -1276644.7
Iteration 1: log likelihood = -849822.09
Iteration 2: log likelihood = -846538.72
Iteration 3: log likelihood = -846524.62
Iteration 4: log likelihood = -846524.62
Logistic regression Number of obs = 1,841,809
Wald chi2(125) = 507020.07
Log likelihood = -846524.62 Prob > chi2 = 0.0000
------------------------------------------------------------------------------------------------------------------------
homeown | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------------------------------------------------+----------------------------------------------------------------
raceth |
4. NHC | .6385632 .027372 23.33 0.000 .5849151 .6922114
5. NHJ | .5653426 .0400141 14.13 0.000 .4869164 .6437688
6. NHF | -.098571 .0338973 -2.91 0.004 -.1650085 -.0321335
7. NHI | -.1735716 .0397069 -4.37 0.000 -.2513957 -.0957475
8. NHK | -.2241101 .0483639 -4.63 0.000 -.3189015 -.1293186
9. NHV | .348966 .0560098 6.23 0.000 .2391888 .4587433
|
1.forborn | -1.316316 .0124516 -105.71 0.000 -1.340721 -1.291912
|
raceth#forborn |
4. NHC#1 | .3350237 .0314141 10.66 0.000 .2734531 .3965943
5. NHJ#1 | -1.139156 .0558045 -20.41 0.000 -1.248531 -1.029781
6. NHF#1 | .0531232 .0382891 1.39 0.165 -.021922 .1281684
7. NHI#1 | .0593582 .0423115 1.40 0.161 -.0235708 .1422871
8. NHK#1 | -.0756405 .0529992 -1.43 0.154 -.179517 .028236
9. NHV#1 | .4663223 .0603573 7.73 0.000 .3480241 .5846204
|
age | .0706146 .0014749 47.88 0.000 .0677239 .0735054
age2 | -.0002098 .0000164 -12.82 0.000 -.0002419 -.0001778
1.female | .006187 .0039075 1.58 0.113 -.0014716 .0138457
|
marst3 |
previously married | -1.198443 .0050531 -237.17 0.000 -1.208347 -1.188539
never married | -1.298763 .0049671 -261.47 0.000 -1.308498 -1.289027
|
educ5 |
HS graduate | .340975 .0098948 34.46 0.000 .3215815 .3603685
Some college | .5482986 .0096026 57.10 0.000 .5294779 .5671193
Bachelor's degree | .9143729 .0098288 93.03 0.000 .8951088 .9336369
Grad+ | .9483004 .0102377 92.63 0.000 .9282348 .968366
|
logfinc | .1916358 .0013543 141.50 0.000 .1889814 .1942903
yrsusa | .0399718 .000417 95.86 0.000 .0391545 .0407891
1.linguiso | -.4252366 .0133153 -31.94 0.000 -.451334 -.3991391
1.mover | -1.289979 .005414 -238.27 0.000 -1.300591 -1.279368
|
met2013 |
10580. albany-schenectady-troy, ny | -3.652022 .0430616 -84.81 0.000 -3.736421 -3.567623
10740. albuquerque, nm | -3.687591 .0502616 -73.37 0.000 -3.786102 -3.58908
...
49660. youngstown-warren-boardman, oh-pa | -3.260858 .0470553 -69.30 0.000 -3.353084 -3.168631
------------------------------------------------------------------------------------------------------------------------
. margins raceth, at(forborn=(0 1))
Predictive margins Number of obs = 1,841,809
Model VCE : OIM
Expression : Pr(homeown), predict()
1._at : forborn = 0
2._at : forborn = 1
------------------------------------------------------------------------------
| Delta-method
| Margin Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_at#raceth |
1#1. NHW | . (not estimable)
1#4. NHC | . (not estimable)
1#5. NHJ | . (not estimable)
1#6. NHF | . (not estimable)
1#7. NHI | . (not estimable)
1#8. NHK | . (not estimable)
1#9. NHV | . (not estimable)
2#1. NHW | . (not estimable)
2#4. NHC | . (not estimable)
2#5. NHJ | . (not estimable)
2#6. NHF | . (not estimable)
2#7. NHI | . (not estimable)
2#8. NHK | . (not estimable)
2#9. NHV | . (not estimable)
------------------------------------------------------------------------------
Code:
. tab raceth forborn if both==1,m
| forborn
raceth | 0 1 | Total
------------+----------------------+----------
1. NHW | 1,564,121 116,852 | 1,680,973
4. NHC | 9,099 40,712 | 49,811
5. NHJ | 4,945 3,989 | 8,934
6. NHF | 4,850 21,479 | 26,329
7. NHI | 3,595 38,288 | 41,883
8. NHK | 2,442 13,908 | 16,350
9. NHV | 1,732 15,797 | 17,529
------------+----------------------+----------
Total | 1,590,784 251,025 | 1,841,809
Thanks!
