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Re: st: negative binomial model in stata


From   Joerg Luedicke <joerg.luedicke@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: negative binomial model in stata
Date   Wed, 2 Nov 2011 14:06:40 -0400

If you cite something, you should provide the full reference. However,
saying that using this model:

 xtgee DV IV controls year, family(nb) corr(sta4) robust

instead of using this model:

xtnbreg DV IV controls,  re

does not make a lot of sense as they are quite different and it
depends on a lot of things which one to chose. The first one (the
-xtgee-) will fit a population averaged model while the latter
(-xtnbreg-) will fit a varying intercept model (aka random intercept
or sometimes just called random effects model). You could obtain the
same result that you get with running the -xtgee- model by using
-xtnbreg-. Just try the following and compare the 2 outputs:

xtnbreg DV IV controls year, pa corr(sta4) vce(robust)


Joerg


On Wed, Nov 2, 2011 at 1:04 PM, Jianhong Chen
<jianhongchen1985@gmail.com> wrote:
> Hi, everyone
>
> I am dealing with longtitudinal panel data using negative binomial
> model. I think random effect would fit. Therefore, I use the following
> command:
>
> xtnbreg DV IV controls,  re.
>
> However, I read another paper which says that " xtnbreg is supposed to
> estimate random and fixed effects negative binomial models, but I
> don’t recommend either. Both of these models have a very peculiar
> parameterization that does not do what it is supposed to do" and this
> paper recommends use one of  the following commands:
>
> nbreg DV IV controls year, cluster(Id)
> xtgee DV IV controls year, family(nb) corr(sta4) robust
>
> What do you think is the best way to go? Thank you very much.
>
> Best,
>
> Jianhong
>
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