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RE: st: RE: Missing standard errors in multinomial logit
Look at your constant for the second option. It's -36. That's bad and I
think it's what's causing your covariance matrix to be trouble.
Something's up. I'd suspect you have some near perfect prediction. You
have A LOT of variables and interactions in this kind of model are
notorious for creating trouble. Start by paring out the vast majority of
your variables and add them in blocks. That will give you a much better
idea of the troublemaker.
JV
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of
[email protected]
Sent: Monday, May 11, 2009 8:26 AM
To: [email protected]
Subject: RE: st: RE: Missing standard errors in multinomial logit
I obtain similar results also without the robust option..
Moreover the standard errors of the estimated coefficient
for the constant are missing: what does it means?
The estimated variance and covariance (listed through the
command vce) for this coefficient are zero.
Thanks
Seerena
> ------------------ Messaggio originale -------------------
> Oggetto: RE: st: RE: Missing standard errors in
> multinomial logit
> Da: "jverkuilen" <[email protected]>
> Data: Lun, 11 Maggio 2009, 2:13 pm
> A: [email protected]
> ----------------------------------------------------------
>
> You asked for clustered robust SEs. You get SEs but no
> overall chi square it looks like (coeffs are a little
> garbled on my screen). This is normal. When Stata doesn't
> report something it is usually a sign that it shouldn't be
> reported. In this case there isn't a valid model chi
> square to report; note the switch to pseudo-likelihood.
>
> One way to screen SEs for a sign of trouble is to see
> whether they are proportional to 1/sqrt(n) (assuming an IV
> and DV that have variances near 1).
>
> -----Original Message-----
> From: [email protected]
> To: [email protected]
> Sent: 5/11/2009 5:10 AM
> Subject: Re: st: RE: Missing standard errors in
> multinomial logit
>
> I estimate:
> mlogit choice sex eta yearsedu y000 unempl y000papa
> lavoramammaspread affitto_r td* reg_*, vce(cluster nquest)
> and the output is:
>
> Multinomial logistic regression Number
> of obs = 9130
> Wald
> chi2(32)
>
>
> =
>
>
>
>
>
>
>
>
>
> .
> Prob
>>
> chi2
>
>
>
>
> =
>
>
>
>
>
>
>
>
>
> .
> Log pseudolikelihood = -3185.8196 Pseudo
> R2 = 0.5029
>
> (Std. Err. adjusted for 5719
> clusters in nquest)
>
------------------------------------------------------------------------
------
> | Robust
> choice | Coef. Std. Err. z P>|z|
> [95% Conf. Interval]
>
-------------+----------------------------------------------------------
------
> Indep.couple |
> sex | -1.259999 .0892111 -14.12 0.000
> -1.43485 -1.085149
> eta | .369897 .0155086 23.85 0.000
> .3395007 .4002934
> yearsedu | -.1782479 .0150689 -11.83 0.000
> -.2077824 -.1487133
> y000 | .0325322 .0062735 5.19 0.000
> .0202364 .0448281
> unempl | -1.387266 .1695346 -8.18 0.000
> -1.719548 -1.054985
> y000papa | .03222 .0059338 5.43 0.000
> .0205899 .0438501
> lavoramamma | 23.84664 1.046417 22.79 0.000
> 21.7957 25.89758
> spread | 31.92757 10.33789 3.09 0.002
> 11.66567 52.18947
> affitto_r | -17.1902 8.191793 -2.10 0.036
> -33.24582 -1.134579
> td1995 | -.7098379 .1494154 -4.75 0.000
> -1.002687 -.416989
> td1998 | -.5893725 .1931463 -3.05 0.002
> -.9679324 -.2108126
> td2000 | -.6813418 .2790856 -2.44 0.015
> -1.228339 -.1343441
> td2002 | -.9640511 .256836 -3.75 0.000
> -1.46744 -.4606618
> reg_NO | 1.055877 .3113467 3.39 0.001
> .4456483 1.666105
> reg_NE | .8436263 .3178704 2.65 0.008
> .2206117 1.466641
> reg_CE | .6105833 .2383532 2.56 0.010
> .1434196 1.077747
> _cons | -33.96454 . . .
> . .
>
-------------+----------------------------------------------------------
------
> Indep.single |
> sex | -.2966189 .1449906 -2.05 0.041
> -.5807953 -.0124424
> eta | .251174 .0260973 9.62 0.000
> .2000242 .3023237
> yearsedu | -.0148035 .0222393 -0.67 0.506
> -.0583918 .0287848
> y000 | .0728665 .0113887 6.40 0.000
> .0505449 .095188
> unempl | -1.143601 .3043513 -3.76 0.000
> -1.740119 -.5470836
> y000papa | -.1020295 .0105506 -9.67 0.000
> -.1227083 -.0813508
> lavoramamma | 25.67025 1.589592 16.15 0.000
> 22.5547 28.78579
> spread | 30.10601 15.7503 1.91 0.056
> -.7640025 60.97603
> affitto_r | .6206542 11.4264 0.05 0.957
> -21.77468 23.01599
> td1995 | -.9829992 .2635091 -3.73 0.000
> -1.499468 -.4665307
> td1998 | -.5831464 .3118048 -1.87 0.061
> -1.194273 .0279797
> td2000 | -.4690283 .4415194 -1.06 0.288
> -1.33439 .3963338
> td2002 | -.4568875 .3842724 -1.19 0.234
> -1.210048 .2962725
> reg_NO | 1.52762 .4547395 3.36 0.001
> .6363469 2.418893
> reg_NE | .9431163 .4625978 2.04 0.041
> .0364414 1.849791
> reg_CE | .8397561 .3691794 2.27 0.023
> .1161779 1.563334
> _cons | -36.50551 . . .
> . .
>
------------------------------------------------------------------------
------
> (choice==Co-reside is the base outcome)
>
>
>>
>> ------------------ Messaggio originale
>> -------------------
>> Oggetto: st: RE: Missing standard errors in multinomial
>> logit
>> Da: "Verkuilen, Jay" <[email protected]>
>> Data: Dom, 10 Maggio 2009, 12:29 am
>> A: [email protected]
>> ----------------------------------------------------------
>>
>> [email protected] wrote:
>>
>>>>I am trying to estimate choices about living
>>>> arrangements
>> by a multinomial logit (mlogit).
>> If I use more than one dummy variable (ex regional
>> dummies, or sex and a dummy for employee) stata fails
>> to
>> compute standard errors of the coefficient of the
>> constant
>> term (they are missing in the output table and zero in
>> the
>> variance/covariance matrix).
>> How can I solve my problem?<<
>>
>> When Stata fails to compute standard errors this is
>> usually a sign of a
>> larger problem with your model. I'd guess that you have
>> near perfect
>> prediction---common when you enter dummies into a
>> multinomial logit---so
>> Stata is able to generate an estimate but it's a nearly
>> useless one. But
>> it could be some other serio
> [truncated by sender]
>
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>
>
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