Re: [R] lmer4 and variable selection

> -- Bert Gunter > Genentech > > > - Original Message- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > On > Behalf Of Andreas Nord > Sent: Monday, August 25, 2008 9:22 AM > To: r-help@r-project.org > Subject: [R] lmer4 and variable selection >

Re: [R] lmer4 and variable selection

On Mon, 25 Aug 2008, jebyrnes wrote: Have you thought about using AIC weights? As long as you are not considering models where you drop your random effects, calculating AIC values (or AICc values) and doing multimodel inference is one way to approach your problem. If you are fitting models wi

Re: [R] lmer4 and variable selection

movies (used to) say: just a friendly warning ... :) -- Bert Gunter Genentech - Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Andreas Nord Sent: Monday, August 25, 2008 9:22 AM To: r-help@r-project.org Subject: [R] lmer4 and variable selection Dear

Re: [R] lmer4 and variable selection

Have you thought about using AIC weights? As long as you are not considering models where you drop your random effects, calculating AIC values (or AICc values) and doing multimodel inference is one way to approach your problem. If you are fitting models with and without random effects, it gets t

[R] lmer4 and variable selection

Dear list, I am currently working with a rather large data set on body temperature regulation in wintering birds. My original model contains quite a few dependent variables, but I do not (of course) wish to keep them all in my final model. I've fitted the following model to the data: > temp.lme