Hi, I'm using a GLM with a quasi binomial error distribution and I would like to do a model selection method similar to step(AIC) to carry out a restricted search for the "best" model. I would like to know which of my 5 predictor variables would be included in the "best" model if I start with a 'full' model (fullbinom in this case). However, AIC can't be calculated on a quasi-binomial model. Is there another similar method I can use?
Here's my R code so far: (AUC ranges from 0 to 1) fail<-1-AUC; succfail<-cbind(AUC, fail) fullbinom<-glm(succfail~variables+log(area)+resolution+model+taxa,family=quasibinomial(link="logit"),data=auc); Thanks in advance, Heather -- Heather Kharouba PhD candidate University of British Columbia ______________________________________________ R-help@r-project.org 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.
