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st: re. Poisson Regression Goodness of Fit Tests

From   "roger webb" <[email protected]>
To   [email protected]
Subject   st: re. Poisson Regression Goodness of Fit Tests
Date   Fri, 3 Oct 2003 12:18:48 +0100

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:

	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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