I have what might seem to be a simple question regarding AIC and parsimony, and yet the answers I have found on the subject are unsatisfactory. So, opinions please.
Here is the scenario: Let's say that one is using AIC for the selection of nested models to avoid multiple LRT comparisons. Should you always choose the model with deltaAIC = 0 as the best? What if there is a model with deltaAIC <2 that has fewer terms? Should it be chosen in the pursuit of parsimony? Or should you report some support for both models? If so, what is the proper language in this case? Let's assume that we are avoiding model averaging. Thanks, Lee -- Lee Davis Graduate Assistant State University of New York College of Environmental Science & Forestry Department of Environmental & Forest Biology 452 Illick Hall, 1 Forestry Drive, Syracuse, NY 13210
