title: Multistate mark-recapture model selection using score tests.
abstract: Although multistate mark-recapture models are recognized as important, they lack a simple model-selection procedure. This article proposes and evaluates a step-up approach to select appropriate models for multistate mark-recapture data using score tests. Only models supported by the data require fitting, so that over-complicated model structures with too many parameters do not need to be considered. Typically only a small number of models are fitted, and the procedure is also able to identify parameter-redundant and near-redundant models. The good performance of the technique is demonstrated using simulation, and the approach is illustrated on a three-region Canada goose data set. In this case, it identifies a new model that is much simpler than the best model previously considered for this application.
authors.affiliation: National Centre for Statistical Ecology, School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury CT2 7NF, UK. R.S.McCrea@kent.ac.uk
authors.forename: Rachel S
authors.initials: RS
authors.lastname: McCrea
authors.forename: Byron J T
authors.initials: BJ
authors.lastname: Morgan
mesh_terms: D000465:Algorithms; D025041:Animal Migration; D000818:Animals; D001699:Biometry / Q000379:methods*; D019352:Censuses; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D008954:Models, Biological; D011157:Population Dynamics