Dear Amanda,
According to "Statistical Computing" by Crawley, p545, you can deal
with overdispersion by any one of 3 ways;
1: Carry out significance tests using "F" rather than "Chi"
in the anova function for comparison of deviances,
2: Use quasipoisson, and specify a variance function, or,
3: Use negative binomial error (see library(MASS), glm.nb).
To answer the second part of your qu, if you do summary(model), you will get the
estimate and s.e. of the log transform of your response variable (log is the
default link).
Cheers,
Martin.
Martin Hoyle,
School of Life and Environmental Sciences,
University of Nottingham,
University Park,
Nottingham,
NG7 2RD,
UK
Webpage: http://myprofile.cos.com/martinhoyle
>>> Amanda Phipps <genepi51 at yahoo.com> 05/01/03 06:04am
>>>
I am fitting a poisson model and it appears to have
overdispersion. I am interested in using the
quasipoisson family (with the glm command). Will this
account for the overdispersion in the model? Is there
an additional method for accounting for a dispersion
parameter not equal to 1 (with the glm command)?
And after fitting the model, how to I obtain the
fitted values and their respective standard errors?
Thank you-
Sarah Watson
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