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# Re: st: different standard errors with gllamm vs. xtmelogit

 From Stas Kolenikov <[email protected]> To [email protected] Subject Re: st: different standard errors with gllamm vs. xtmelogit Date Tue, 26 Oct 2010 10:56:09 -0500

```Are the likelihoods the same? Sometimes I find small differences in
the likelihood, too, which is indicative of lack of accuracy (in at
least one program). The first thing I would do would be to increase
the number of integration points (in both models) to say 15 and see if
the results change. In most -gllamm- examples from Sophia, the number
of integration points is even, although I don't know if there any
particular reason for that.

On Tue, Oct 26, 2010 at 8:11 AM, de Vries, Robert
<[email protected]> wrote:
> Hello everyone. I'm having a weird problem with gllamm and xtmelogit when r= unning a fairly simple 2-level random intercepts model.
>
> The model is predicting a binary health outcome from 1 level 2 variable (me=
> angini) and several level 1 variables. It is a sample if 5,4410 people in 1=
> 6 countries, with 'country' as the level 2 cluster.
>
> The xtmelogit model looks like this:
>
> xi: xtmelogit poorhealth meangini age47 gndr i.education if poorhealth_samp=
> le=3D=3D1 || country1 :
>
> (note that the number of integration points is left at the default of 7)
>
> It converges fine on iteration 3 with a log likelihood if -15046.989. The r= esult I am interested in is for meangini and in this model it is -0.030 (SE=  =3D 0.035)
>
> The gllamm model is identical (as far as I can tell)
>
> xi: gllamm poorhealth meangini age47 gndr i.education if poorhealth_sample= =3D=3D1, i(country1) nip(7) link(logit) f(binomial)
>
> However the coefficient for the same variable is different (-0.041). And th= e Standard Error (0.0043) is over 8 times smaller.
>
> This is obviously extremely important in interpreting the statistical signi= ficance of the results so I'd appreciate any help anyone might be able to o= ffer as to what's going on.
>
> Cheers
> Rob
>
>
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>

--
Stas Kolenikov, also found at http://stas.kolenikov.name
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