The effects of high detection probabilities on model selection in paired release-recapture studies in the era of electronic tagging studies

John R Skalski, Adam G Seaburg, Rebecca A Buchanan
2013 Animal Biotelemetry  
Acoustic-tag studies with their high to very high detection rates defy traditional statistical wisdom regarding analysis of tagging studies. Conventional wisdom has been to use a parsimonious model with the fewest parameters that adequately describes the data to estimate survival parameters in release-recapture studies in order to find a reasonable trade-off between precision and accuracy. This quest has generated considerable debate in the statistical community on how to best accomplish this
more » ... t accomplish this task. Among the debated options are likelihood ratio tests, Bayesian information criterion, Akaike information criterion, and model averaging. Results: Our Monte Carlo simulation studies of paired release-recapture, acoustic-tag investigations indicate precision is the same if a fully parameterized or a reduced parameter model is used for data analysis if detection probabilities are very high. In addition, the fully parameterized model is robust to heterogeneous survival and detection processes, while a reduced parameter model may be sensitive to misspecification. Conclusions: Use fully parameterized, paired release-recapture models when detection probabilities are very high (≥0.90) to analyze acoustic-tagging data in order to retain both robustness and precision, and without the subjectivity and ambiguity introduced by the choice and application of model selection techniques.
doi:10.1186/2050-3385-1-12 fatcat:5ez4wmbpnzdu7en7awdl7itg4e