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Re: st: Multinomial logistic regression under R and Stata
Tak Wing Chan found some differences in the standard errors of ceratin parameter
estimates for a particular multinomial logistic model fitted by -mlogit- and by the
corresponding command in R.
As Scott Merryman pointed out in, Brian Ripley, posting on the R Help list in response
to Tak Wing's posting about the discrepancies, mentioned that the Hauck-Donner
Phenomenon, which I had never heard of, is among the possibilities for an explanation
of the discrepancies between Stata and R: "R uses the observed information matrix for
the standard errors. It is also possible to use the expected (Fisher) information matrix.
Where they differ, the observed one is generally regarded as a better choice, especially
when as here the curvature is measured over a reasonably-sized neighbourhood. . . .
such differences can [also] be caused by the Hauck-Donner effect and lack of
convergence, so it is almost always worth playing with the convergence criteria."
I'm not certain that it matters, if I'm not mistaken, since the canonical link is used, but I
believe that Stata uses the observed information matrix by default with -mlogit-,
anyway. So that doesn't appear to be the root of the problem. If the likelihood-
maximization methods and convergence criteria are similar (and these can be
checked), then that leaves the "Hauck-Donner effect" as a suspect.