I always use the likelihood ratio test when evaluating which predictors to
include in a model. During preliminary analysis I'll accept "highly"
significant p-values based Z statitics (or t), but not for fine-tuning the final
model.
Joe Hilbe
================================================
thanks. I was indeed using pweight in nbreg regression. Then it seems the
Wald test will be appropriate. But I checked the STATA document and it
says: "after the manuals were printed, we revisited this subject and
discovered that we did not, in fact, want to include this test (Wald). The
likelihood-ratio test is the only test that one should consider in these
limiting cases". So do I simply use the wald test reported above the
coefficient table?
Thanks again.
> At 03:40 PM 3/10/2005 -0500, [email protected] wrote:
>>Hi, all,
>>
>>Usually there is a log likelikhood ratio test statistics reported after a
>>negative binominal regression (I ran possion regression first, and then
>>used 'nbreg' regression), and sometimes the Z score for alpha is reported
>>too. But in my case, I didn't see the ratio reported after the
>>regression, and there is no z score for alpha. Then I tried to use
>>'lrtest' after the model, but it says
>>"lrtest not valid after robust
>>specify force option to perform test anyway".
>>
>>So I put 'force' in option, but it still didn't give me the result.
>>
>>Can anybody tell me what's going on?
>
> Sounds like you used the robust option. There is some discussion of this
> on p. 28 of the Stata 8 Survey Data Manual. It says that "pseudo-maximum
> likelihood methods" (which get used with robust standard errors) are not
> "true likelihoods" and hence "standard LR tests are no longer valid".
>
> For more, see the FAQ "Why should I not do a likelihood-ratio test after
> an
> ML estimation (e.g., logit, probit) with clustering or pweights?" at
>
> http://www.stata.com/support/faqs/stat/lrtest.html
>
> Other related FAQs are at
>
> http://www.stata.com/support/faqs/stat/#robust
>
>
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
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Ying Wang
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