st: RE: testing nest models in Poisson regression

["Visintainer, Paul" <Paul.Visintainer@baystatehealth.org>]

I think I may have answered my own question.  The block of indicators can be tested with a Wald test using the -test- command after the full model.  If the indicators are modeled with "i.var" syntax, then all levels of the indicators can be entered in the -test- command.  E.g., if there are 4 indicators, 3 will enter the model with one as the reference category (e.g, categories 2, 3, and 4).

Test will still allow all 4 to be tested.

. test 1.var=2.var=3.var=4.var

This will yield a test with 3 degrees of freedom.


Thanks.

-p

________________________________________________
Paul F. Visintainer, PhD
Springfield, MA 01199



-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Visintainer, Paul
Sent: Thursday, August 26, 2010 11:51 AM
To: 'statalist@hsphsun2.harvard.edu'
Subject: st: testing nest models in Poisson regression 

I'm estimating two models (one nested within the other) with poisson regression with the robust option.  I'd like to test whether a block of indicator variables is significant in the model.  If I were using logistic regression, I would use the -lrtest-.  However, for Poisson models with the robust option, the lrtest is invalid.  In fact, with the robust option, the outputs report a Wald chi-square, rather than a LR chi-square, for the test of the model against the null.

Would it be valid to test the difference in the models by taking the difference between the two model Wald chi-squares and the difference between the model d.f.s and using the chi-square distribution?  (I'm assuming that the difference between two chi-squares is a chi-square with the appropriate degrees of freedom).  

Any suggestions would be appreciated.

Thanks.

________________________________________________
Paul F. Visintainer, PhD
Springfield, MA 01199

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