On Mon, 13 Nov 2006, Murray Jorgensen wrote: > I am wondering if stepAIC in the MASS library may be used for model > selection in an overdispersed Poisson situation. What I thought of doing > was to get an estimate of the overdispersion parameter phi from fitting > a model with all or most of the available predictors (we have a large > number of observations so this should not be problematical) and then use > stepAIC with scale = phi. Should this be OK?
Well no, as that quasi-Poisson model does not have an AIC. Remember AIC assumes maximum likelihood fitting, and you don't have a likelihood here (even for fixed phi). The problem is that an 'overdispersed Poisson situation' is a situation, not a model (in the usual sense of a probability measure over possible outcomes). You could use a negative binomial GLM (with fixed theta). -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
