Kenneth P. Burnham Thomas R. Stanley 1998 <p><span>Specification of an appropriate model is critical to valid statistical inference. Given the “true model” for the data is unknown, the goal of model selection is to select a plausible approximating model that balances model bias and sampling variance. Model selection based on information criteria such as AIC or its variant AIC</span>_c<span>, or criteria like CAIC, has proven useful in a variety of contexts including the analysis of open-population capture-recapture data. These criteria have not been intensively evaluated for closed-population capture-recapture models, which are integer parameter models used to estimate population size (</span><i>N</i><span>), and there is concern that they will not perform well. To address this concern, we evaluated AIC, AIC</span>_c<span>, and CAIC model selection for closed-population capture-recapture models by empirically assessing the quality of inference for the population size parameter&nbsp;</span><i>N</i><span>. We found that AIC-, AIC</span>_c<span>-, and CAIC-selected models had smaller relative mean squared errors than randomly selected models, but that confidence interval coverage on&nbsp;</span><i>N</i><span>&nbsp;was poor unless unconditional variance estimates (which incorporate model uncertainty) were used to compute confidence intervals. Overall, AIC and AIC</span>_c<span>&nbsp;outperformed CAIC, and are preferred to CAIC for selection among the closed-population capture-recapture models we investigated. A model averaging approach to estimation, using AIC, AIC</span>_c<span>, or CAIC to estimate weights, was also investigated and proved superior to estimation using AIC-, AIC</span>_c<span>-, or CAIC-selected models. Our results suggested that, for model averaging, AIC or AIC</span>_c<span>&nbsp;should be favored over CAIC for estimating weights.</span></p> application/pdf 10.1002/(SICI)1521-4036(199808)40:4%3C475::AID-BIMJ475%3E3.0.CO;2-%23 en Wiley Information-theoretic model selection and model averaging for closed-population capture-recapture studies article