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Re: st: Problem with margins after logit on a person period data
From
Richard Williams <[email protected]>
To
[email protected], [email protected]
Subject
Re: st: Problem with margins after logit on a person period data
Date
Wed, 08 Jun 2011 19:17:37 -0500
I don't think margins likes it when you use the noconstant option. Is
it really necessary for your model?
At 05:08 PM 6/8/2011, Urmi Bhattacharya wrote:
Dear Statalisters,
I am running the following logit on a person-period data
logit school_left childage i.childfemale i.urban i.scstobc
i.casteother i.dadp i.dadm i.momp i.momm wagep wage5 wage8 w
> age9 distp distm disth percapcons durat1 durat2 durat3 durat4
durat5 durat6 durat7 durat8 durat9 durat10 durat11, nocon
> s nolog
Logistic regression Number of obs = 47569
Wald
chi2(28) = 14601.42
Log likelihood = -14502.393 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
school_left | Coef. Std. Err. z P>|z| [95%
Conf. Interval]
-------------+----------------------------------------------------------------
childage
| -.1413654 .006069 -23.29 0.000 -.1532605 -.1294703
1.childfem~e | .0212387 .0306462 0.69 0.488 -.0388266 .0813041
1.urban
| .0124911 .0368072 0.34 0.734 -.0596497 .0846319
1.scstobc
| 1.972676 .1234074 15.99 0.000 1.730802 2.21455
1.casteother | 1.883233 .125722 14.98 0.000 1.636822 2.129643
1.dadp
| .680585 .044327 15.35 0.000 .5937057 .7674643
1.dadm
| .3872552 .0506982 7.64 0.000 .2878886 .4866217
1.momp
| 1.351053 .0835161 16.18 0.000 1.187364 1.514741
1.momm
| .9494066 .0918146 10.34 0.000 .7694532 1.12936
wagep
| -.0281962 .0061845 -4.56 0.000 -.0403176 -.0160748
wage5
| -.0040992 .0045604 -0.90 0.369 -.0130373 .004839
wage8
| .021027 .0043869 4.79 0.000 .0124289 .0296251
wage9
| .0159427 .0022335 7.14 0.000 .0115652 .0203203
distp
| -.0355589 .0162329 -2.19 0.028 -.0673748 -.0037431
distm
| -.0024083 .0112658 -0.21 0.831 -.0244888 .0196722
disth
| .0186932 .0039384 4.75 0.000 .010974 .0264124
percapcons
| -.0001459 .0000278 -5.26 0.000 -.0002003 -.0000915
durat1
| -5.771466 .1406919 -41.02 0.000 -6.047217 -5.495715
durat2
| -4.947835 .1222363 -40.48 0.000 -5.187414 -4.708256
durat3
| -4.690019 .1193602 -39.29 0.000 -4.923961 -4.456078
durat4
| -4.054464 .1132586 -35.80 0.000 -4.276447 -3.832481
durat5
| -3.055883 .1082449 -28.23 0.000 -3.268039 -2.843727
durat6
| -3.560284 .1130896 -31.48 0.000 -3.781936 -3.338633
durat7
| -2.825943 .1099477 -25.70 0.000 -3.041436 -2.610449
durat8
| -2.238741 .1094063 -20.46 0.000 -2.453173 -2.024308
durat9
| -1.427979 .1099217 -12.99 0.000 -1.643421 -1.212536
durat10
| -.3967904 .1152271 -3.44 0.001 -.6226313 -.1709495
durat11
| -2.168164 .1486318 -14.59 0.000 -2.459477 -1.876851
------------------------------------------------------------------------------
.
end of do-file
Since I am interested in the marginal effects of the variables on the
probability of hazard,
I do
margins,dydx(*)
But this gives me the following output
margins,dydx(*)
Average marginal effects Number of obs = 47569
Model VCE : OIM
Expression : Pr(school_left), predict()
dy/dx w.r.t. : childage 1.childfemale 1.urban 1.scstobc 1.casteother
1.dadp 1.dadm 1.momp 1.momm wagep wage5 wage8
wage9 distp distm disth percapcons durat1 durat2 durat3
durat4 durat5 durat6 durat7 durat8 durat9
durat10 durat11
------------------------------------------------------------------------------
| Delta-method
| dy/dx Std. Err. z P>|z| [95%
Conf. Interval]
-------------+----------------------------------------------------------------
childage | (not estimable)
1.childfem~e | (not estimable)
1.urban | (not estimable)
1.scstobc | (not estimable)
1.casteother | (not estimable)
1.dadp | (not estimable)
1.dadm | (not estimable)
1.momp | (not estimable)
1.momm | (not estimable)
wagep | (not estimable)
wage5 | (not estimable)
wage8 | (not estimable)
wage9 | (not estimable)
distp | (not estimable)
distm | (not estimable)
disth | (not estimable)
percapcons | (not estimable)
durat1 | (not estimable)
durat2 | (not estimable)
durat3 | (not estimable)
durat4 | (not estimable)
durat5 | (not estimable)
durat6 | (not estimable)
durat7 | (not estimable)
durat8 | (not estimable)
durat9 | (not estimable)
durat10 | (not estimable)
durat11 | (not estimable)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
Can someone explain what am I doing wrong? How do I get the marginal
effects after running the logit?
Best
Urmi
*
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-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: [email protected]
WWW: http://www.nd.edu/~rwilliam
*
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* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/