Multistate mark-recapture model selection using score tests
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 fit...
| Published in: | Biometrics |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | unknown |
| Published: |
2011
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| Subjects: | |
| Online Access: | https://kar.kent.ac.uk/27602/ https://doi.org/10.1111/j.1541-0420.2010.01421.x |
| Summary: | 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. |
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