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st: RE: Negative Binomial Models


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Negative Binomial Models
Date   Thu, 14 Oct 2004 00:43:31 +0100

Should or should not? 

I'd like to hear the grounds for that. I find it 
difficult to believe that any such criterion tenet
aquam. You should use a negative binomial distribution 
whenever fitted probabilities are close to observed
probabilities. 

The underlying frequencies are not that germane. 
But if the total number of individuals in the sample 
is large, at least some cell frequencies are likely 
to be. In fact, to get a good handle on probabilities
in the tail, a very large sample is a really good idea. 

I'm interested in comments on this. If you type 

. ssc type nbfit.hlp 

there's a worked example in which the peak frequency 
was 807. 

Nick 
n.j.cox@durham.ac.uk 

> -----Original Message-----
> From: Nick Cox 
> Sent: 14 October 2004 00:38
> To: 'statalist@hsphsun2.harvard.edu'
> Subject: RE: Negative Binomial Models
> 
> 
> 
> 
> Nick 
> n.j.cox@durham.ac.uk 
> 
> > -----Original Message-----
> > From: owner-statalist@hsphsun2.harvard.edu
> > [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of MacDonald,
> > John
> > Sent: 14 October 2004 00:23
> > To: statalist@hsphsun2.harvard.edu
> > Subject: st: Negative Binomial Models
> > 
> > 
> > Is there a maximum number of counts one should not exceed 
> > when using the negative binomial model?  Even if there is a 
> > adjustment for exposure (e.g., rate of homicides in a city).  
> > I have a data set with over 200 homicides in some cities and 
> > I saw a reference in an article of American Journal of 
> > Sociology to Maddala's 1977 econometrics textbook that said 
> > you should exceed 50 counts.  Is this true?
> > 
> > 
> > 
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