st: re. Poisson Regression Goodness of Fit Tests

[Michel Camus <mcamus@videotron.ca>]

First, you should have typed "search overdispersion , all". |:-()
-nbreg- is your solution. Simply replace "poissson" by "nbreg" in your 
model, then check the "Likelihood-ratio test of alpha=0".
This is one real test for overdispersion. [ Is this not easy enough 
relative to SAS?  /:-)  ]
Still, your extreme -poisgof- GOF chi2 indicates that the Poisson 
regrssion model is inappropriate.
Read -nbreg- section in Stata Reference Manual N-R.
You may want to explore reasons for overdispersion by using -gnbreg-.
Read FAQ for both overdispersion and zero-inflated data if this 
applies:  http://www.stata.com/support/faqs/stat/nbreg.html

Michel Camus
===========
roger webb wrote:


> Dear Statalist
>
> I'm generating Poisson regression models with an aggregated data 
> set (i.e. each record in the data set represents a stratum of 
> aggregated numbers of deaths and person-years of observation).
>
> I wish to check that the models are not over-dispersed. The manual 
> tells me that I can use either the 'poisgof' or the 'poisgof, pearson' 
> command. These produce the following contradictory results:
>
> poisgof
> 	
> 	Goodness-of-fit chi2 = 1191.579
> 	Prob > chi2 (5304) = 1.0000
>
> poisgof, pearson
>
> 	Goodness-of-fit chi2 = 29207.21
> 	Prob > chi2 (5304) = 0.0000
>
> A colleague has told me that these results have no meaning for my 
> data set, because the degrees of freedon are incorrect (I think). He 
> says that I should instead apply the Breslow adjusted score test 
> (Breslow NE. Generalized linear models: checking assumptions 
> and strengthening conclusion. Statistica Applicata 1996; 8: 23-41). 
> My colleague says this test is unavailable in standard stats 
> packages, but he has programmed SAS to perform the test. He 
> thinks it would take me 2 to 3 weeks to write a similar programme 
> in Stata. Can anyone please advise me further on this? Has 
> anyone attempted to programme Stata to run the adjusted score 
> test? Are there any alternatives?
>
> Thanks in advance
>
> Roger Webb
> University of Manchester (UK)
> +44 161 275 0728
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>
>  
--

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Michel Camus, Ph.D.

�pid�miologue, Div. Biostatistique et �pid�miologie, DGSESC, Sant� Canada

Epidemiologist, Biostatistics and Epidemiology Div., HECSB, Health Canada

Courriel / e-mail : mcamus@videotron.ca <mailto:mcamus@videotron.ca>

T�l�phone / phone     :    (514) 850-0157

T�l�copieur / fax        :    (514) 850-0836

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