Random effects and shrinkage estimation in capture-recapture models

We discuss the analysis of random e ects in capture-recapture models, and outline Bayesian and frequentists approaches to their analysis. Under a nor mal model, random e ects estimators derived from Bayesian or frequentist considerations have a common for m as shrinkage estimators. We discuss some of the difficulties of analysing random e ects using traditional methods, and argue that a Bayesian formulation provides a rigorous framework for dealing with these difficulties. In capture-recapture models, random e ects may provide a parsimonious compromise between constant and completely time-dependent models for the parameters (e. g. survival probability). We consider application of random e ects to band-recovery models, although the principles apply to more general situations, such as Cormack-Jolly-Seber models. We illustrate these ideas using a commonly analysed band recovery data set.