Studies which measure animals' positions over time are a vital tool in understanding the process of resource selection by animals. By comparing a sample of locations used by animals with a sample of available points, the types of locations preferred by animals can be analysed using logistic regression. Random effects logistic regression has been proposed to deal with the repeated measurements observed for each animal, but we find that this is not feasible in studies where the sample of available points cannot readily be matched to specific animals. Instead, this paper investigates the use of marginal logistic models with robust variance estimators, using a study of Australian bush rats as a case study. Simulation is used to check the properties of the approach and to explore alternative designs.
Available at: http://works.bepress.com/robert_clark/23/