on 10/31/2008 01:07 PM Antonio.Gasparrini at lshtm.ac.uk
wrote:> Dear fellows,
>
> I'm trying to extract the AIC statistic from a GLM model with
quasipoisson link.
> The formula I'm referring to is
>
> AIC = -2(maximum loglik) + 2df * phi
>
> with phi the overdispersion parameter, as reported in:
>
> Peng et al., Model choice in time series studies os air pollution and
mortality. J R Stat Soc A, 2006; 162: pag 190.
>
> Unfortunately, the function logLik doesn't work for a quasipoisson
link.
> Do you know a fast method to extract the AIC for these models?
>
> Thanks in advance
I was under the impression that there is no log likelihood for quasi*
family models, thus no AIC, which is why they are not calculated/printed
in the glm() summary outputs.
If you want to model overdispersed data and need the AIC, you should
look at glm.nb() in MASS for a negative binomial model:
library(MASS)
?glm.nb
This would also avail you of the anova.glm() methods for comparing
models, which the quasi* families would not.
You might also want to look at:
http://cran.r-project.org/web/packages/pscl/vignettes/countreg.pdf
which is the vignette from the pscl package.
HTH,
Marc Schwartz