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Re: st: AW: Poisson and negative binomial regression


From   "Mamopeli Matooane" <mmatooane@csir.co.za>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: AW: Poisson and negative binomial regression
Date   Wed, 19 Aug 2009 09:02:15 +0200

Martin 

Thanks for the links. 
The 1 refers to the dispersion statistic (1/DF)  

>>> "Martin Weiss" <martin.weiss1@gmx.de> 18/08/2009 09:57 >>>

<> 

See http://www.stata.com/statalist/archive/2008-12/msg00843.html and
Cameron
and Trivedi (2009), chap. 17, http://www.stata-press.com/books/mus.html


The cut-off for overdispersion depends on your chosen significance
level for
the "Likelihood-ratio test of alpha=0" at the bottom of -nbreg- output
in
Stata. What is the "1" you are referring to in your last sentence?


HTH
Martin


-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu 
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Mamopeli
Matooane
Gesendet: Dienstag, 18. August 2009 09:47
An: statalist@hsphsun2.harvard.edu 
Betreff: st: Poisson and negative binomial regression

I have count data - time-activity data (dependant variable) and
categorical
data e.g. gender, education, employment  and others (Independant
variables).
I have applied poisson and NBR and get similar results in terms of
coefficients, and p-values. There's a slight improvement in standard
errors
with NBR.
Applying NBR does not however eliminate the problem of underdispserion
in
the data. How does one address underdispersion and what is the cut off
point
from 1 to say there's underdisprsion/overdispersion 




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