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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