Hi, I found the book Mixed effects models and Extensions in Ecology With R by Zuure et al. Was useful. They have a good example of model comparison. Rebecca
On Wed, Apr 21, 2010 at 2:00 AM, Helen Bothwell <[email protected]> wrote: > In working with AICc model averaging and selection, I am not sure what the > precedence is for choosing a subset of models to compare. We are > investigating genetic loci under supposed adaptive selection pressure from > environmental variables. We have no prior expectations of which specific > variables may be influencing certain loci and can not a priori reduce > models for comparison. Our data set includes a large number of plausible > explanatory environmental variables. We initially compared a subset of > models with delta AIC values ranging from 0-10. I have found information > saying that delta AIC values from 0-2 indicate that a given model should > be considered within the range of plausible models for the set under > investigation. Coding in R for a given locus, when I change the input > call for the subset of deltas to compare (I've tried 10, 5, and 3) the > Deviance, AICc, and Delta of the various models do not change, however the > weights given to the various models do change as do the values of Relative > Variable Importance. For example, with input delta <10, the best model > weight is 0.03, whereas it is 0.074 with input delta <3. Is there a > precedence for how many models to compare, a subset Delta AICc cut-off > line for model comparison? Any feedback is much appreciated! > > Sincerely, > Helen Bothwell >
