A Bayesian multinomial model for analyzing categorical habitat selection data

Modeling the number of uses of discrete habitat types by animals with a multinomial distribution, we illustrate the use of Bayesian methods to estimate selection. An advantage of this approach in assessing selection is the construction of credibility intervals that do not rely on large sample normal theory. In addition, credibility intervals for ranked selection of habitats are easily obtained. Bayes factors and Bayesian p values (posterior predictive values) are used to test the hypothesis of selection for each animal, test selection across all animals and for multiple comparisons among habitats. We compare our method to alternative methods for a real dataset. Freely available WinBUGS software is used to fit the model and test hypotheses.