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Re: st: different standard errors with gllamm vs. xtmelogit
From
[email protected] (Roberto G. Gutierrez, StataCorp)
To
[email protected]
Subject
Re: st: different standard errors with gllamm vs. xtmelogit
Date
Wed, 27 Oct 2010 09:37:42 -0500
Robert de Vries, Robert <[email protected]> is having some
difficulty reconciling results between -gllamm- and -xtmelogit-. He writes:
> The log likelihood's with 7 integration points are:
> Xtmelogit: -15047.008
> Gllamm: -15056.655
> I tried increasing the number of integration points to 15 as you suggested.
> This yielded yet more strange results.
> The gllamm and xtmelogit likelihood's are more similar for these models, but
> with gllamm's still being slightly higher (15047.916 vs. 15059.682)
> The standard errors of the coefficient I'm interested in are still wildly
> different between gllamm and xtmelogit, but now so is the coefficient
> itself:
> Xtmelogit: -.034(.039663)
> Gllamm: -.0045(.004751)
> Most of the other coefficients and standard errors are almost identical
> between the two models so initially I thought it might just be a problem
> with the level 2 variable I've been discussing above. However the
> coefficients and SE's of the individual l evel binary gender variable are
> also very different between gllamm and xtmelogit.
In a previous message in this thread Robert showed an example of a -gllamm-
command that he issued, and this command did not include the -adapt- option.
-adapt- tells -gllamm- to use adaptive rather than standard Gaussian
quadrature. Because -xtmelogit- also uses adaptive Gaussian quadrature
(albeit in a slightly different form), using -adapt- with -gllamm- should help
bring the results more in line with one another.
Of course, if the difference persists Robert can feel free to email me with
the data and I can take a closer look.
--Bobby
[email protected]
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