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Re: st: ml command and chi-square tests


From   Richard Williams <Richard.A.Williams.5@nd.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: ml command and chi-square tests
Date   Fri, 01 Apr 2005 11:42:19 -0500

At 05:45 PM 3/25/2005 -0600, Jeff Pitblado, StataCorp LP wrote:
This restriction was added when Stata 8.1 was released (01jul2003).  It was
added to prevent -ml- from producing an invalid likelihood ratio test, given
its theoretical requirements and the possibility for boundary conditions
imposed by constraints (see the discussion of the likelihood ratio test for
alpha=0 in [R] nbreg).

We considered it safer to produce the Wald test when constraints are supplied
than try to recover from all the possible cases where the standard likelihood
ratio test is not applicable.

As Richard points out, you can still use the -lrtest- command to produce a
likelihood ratio test.
Returning to the subject of LR tests when constraints are imposed - are their criteria by which I can decide whether an LR test is or is not appropriate when constraints are imposed? The constraints I am most likely to impose are two or more betas are equal (either within or across equations) or else one or more
betas = 0. These are generally things I could do myself by estimating two models, e.g. have a model with the variable in and another model without it; have a model with the two variables entered separately and another model which uses their sum. So, my guess is that a LR chi-square test will be appropriate with such constraints. But, if anyone has more guidance on this, I would appreciate it.

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Richard Williams, Notre Dame Dept of Sociology
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