If you're not interested in fitting caribou-specific responses, you can use beta-binomial logistic models. There are several package available for this purpose on CRAN, among which aod. Because these models are fitted using maximum-likelihood methods, you can use AIC (or other information criteria) to compare different models.
Best, Renaud 2006/1/30, [EMAIL PROTECTED] <[EMAIL PROTECTED]>: > > > I am creating habitat selection models for caribou and other species with > data collected from GPS collars. In my current situation the radio-collars > recorded the locations of 30 caribou every 6 hours. I am then comparing > resources used at caribou locations to random locations using logistic > regression (standard habitat analysis). > > The data is therefore highly autocorrelated and this causes Type I error > two ways – small standard errors around beta-coefficients and > over-paramaterization during model selection. Robust standard errors are > easily calculated by block-bootstrapping the data using "animal" as a > cluster with the Design library, however I haven't found a satisfactory > solution for model selection. > > A couple options are: > 1. Using QAIC where the deviance is divided by a variance inflation factor > (Burnham & Anderson). However, this VIF can vary greatly depending on the > data set and the set of covariates used in the global model. > 2. Manual forward stepwise regression using both changes in deviance and > robust p-values for the beta-coefficients. > > I have been looking for a solution to this problem for a couple years and > would appreciate any advice. > > Jesse > > ______________________________________________ > 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 -- Renaud LANCELOT Département Elevage et Médecine Vétérinaire (EMVT) du CIRAD Directeur adjoint chargé des affaires scientifiques CIRAD, Animal Production and Veterinary Medicine Department Deputy director for scientific affairs Campus international de Baillarguet TA 30 / B (Bât. B, Bur. 214) 34398 Montpellier Cedex 5 - France Tél +33 (0)4 67 59 37 17 Secr. +33 (0)4 67 59 39 04 Fax +33 (0)4 67 59 37 95 ______________________________________________ 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
