Thanks for your great and helpfull answer.
Have a nice evening.
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> Gesendet: 28.02.08 15:28:22
> An: [email protected]
> Betreff: st: RE: ST: Basic question to Count Data Models
>
> Under-dispersion can be modeled using a generalized Poisson regression, and
> has also been modeled using a 2-parameter log-gamma model. A double Poisson
> model has also been used, but there is no software support for it that I know
> of. Negative binomial only models overdispersion. Both the generalized
> Poisson and 2-parameter log-gamma models are discussed in some detail in
>
> Hilbe, Joseph M (2007), Negative Binomial Regression, Cambridge University
> Press
>
> and is also described in
>
> Hardin, J.W and J.M. Hilbe (2007), Generalized Linear Models and Extensions,
> 2nd edition, Stata Press.
>
> Again, you can get the commands to estimate under-dispersion by downloading
> them from the book's web site.
>
> Under-dispersion is quite rare in real data, but does occur. Actually, if
> you don't have the above software, you can adjust the standard errors of the
> under-dispersed Poisson model by scaling based on the Pearson dispersion sta
> tistic. Simulation studies I have done have shown that it generally does a good
> job in appropriately adjusting the under-dispersed model.
>
> Joseph Hilbe
>
>
>
> Date: Wed, 27 Feb 2008 12:57:52 -0500
> From: "Austin Nichols" <[email protected]>
> Subject: Re: st: Basic question to Count Data Models
>
>
> > Another problem: Someone told me that "dispersion" or "under-dispersion"
> > might be a problem with a Count Data Model. I did some research but
> couldnŽt
> > find anyhting about that. Does anyone of you know whether this is true?
> And if
> > so, can you give me a hint or literature suggestion, what
> "under-dispersion"
> > is and how I could face it in my problem?
> >
> > Thanks a lot,
> > Markus.
> >
>
>
>
>
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