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st: RE: ST: Basic question to Count Data Models


From   Jhilbe@aol.com
To   statalist@hsphsun2.harvard.edu
Subject   st: RE: ST: Basic question to Count Data Models
Date   Thu, 28 Feb 2008 09:24:59 EST

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"  <austinnichols@gmail.com>
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 
couldnīt
> 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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