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Analysis of capture-recapture models with individual covariates using data augmentation

Biometrics

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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.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Analysis of capture-recapture models with individual covariates using data augmentation
Series title:
Biometrics
Volume
65
Issue:
1
Year Published:
2009
Language:
English
Contributing office(s):
Patuxent Wildlife Research Center
Description:
267-274
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Biometrics
First page:
267
Last page:
274