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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:

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 moreThis 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.

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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