Analysis of capture–recapture models with individual covariates using data augmentation
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Abstract
I consider the analysis of capture–recapture models with individual covariates that influence detection probability. Bayesian analysis of the joint likelihood is carried out using a flexible data augmentation scheme that facilitates analysis by Markov chain Monte Carlo methods, and a simple and straightforward implementation in freely available software. This approach is applied to a study of meadow voles (Microtus pennsylvanicus) in which auxiliary data on a continuous covariate (body mass) are recorded, and it is thought that detection probability is related to body mass. In a second example, the model is applied to an aerial waterfowl survey in which a double‐observer protocol is used. The fundamental unit of observation is the cluster of individual birds, and the size of the cluster (a discrete covariate) is used as a covariate on detection probability.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Analysis of capture–recapture models with individual covariates using data augmentation |
| Series title | Biometrics |
| DOI | 10.1111/j.1541-0420.2008.01038.x |
| Volume | 65 |
| Issue | 1 |
| Year Published | 2009 |
| Language | English |
| Publisher | Wiley |
| Contributing office(s) | Patuxent Wildlife Research Center |
| Description | 8 p. |
| First page | 267 |
| Last page | 274 |
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