Anita and Rachel have had a paper accepted in Journal of Agricultural Biological and Environmental Statistics.<\/p>\n
A Test of Positive Association for Detecting Heterogeneity in Capture for Capture\u2013Recapture Data<\/p>\n
Anita Jeyam,\u00a0Rachel S. McCrea,\u00a0Thomas Bregnballe,\u00a0Morten Frederiksen and\u00a0Roger Pradel<\/p>\n
The Cormack\u2013Jolly\u2013Seber (CJS) model assumes that all marked animals have equal recapture probabilities at each sampling occasion, but heterogeneity in capture often occurs and should be taken into account to avoid biases in parameter estimates. Although diagnostic tests are generally used to detect trap-dependence or transience and assess the overall fit of the model, heterogeneity in capture is not routinely tested for. In order to detect and identify this phenomenon in a CJS framework, we propose a test of positive association between previous and future encounters using Goodman\u2013Kruskal\u2019s gamma. This test is based solely on the raw capture histories and makes no assumption on model structure. The development of the test is motivated by a dataset of Sandwich terns (Thalasseus sandvicensis), and we use the test to formally show that they exhibit heterogeneity in capture. We use simulation to assess the performance of the test in the detection of heterogeneity in capture, compared to existing and corrected diagnostic goodness-of-fit tests, Leslie\u2019s test of equal catchability and Carothers\u2019 extension of the Leslie test. The test of positive association is easy to use and produces good results, demonstrating high power to detect heterogeneity in capture. We recommend using this new test prior to model fitting as the outcome will guide the model-building process and help draw more accurate biological conclusions.<\/p>\n