Estimation of capture probabilities using generalized estimating equations and mixed effects approaches
Article first published online: 10 MAR 2014
© 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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Ecology and Evolution
Volume 4, Issue 7, pages 1158–1165, April 2014
How to Cite
Ecology and Evolution 2014; 4(7):1158–1165
- Issue published online: 7 APR 2014
- Article first published online: 10 MAR 2014
- Manuscript Accepted: 23 JAN 2014
- Manuscript Received: 14 JAN 2014
- EU Erasmus Mundus Action 2
- Fundacao Nacional para a Ciencia e Tecnologia (FCT). Grant Number: PEst-OE/MAT/UI0117/2011
- Closed population;
- generalized linear models;
- generalized linear mixed models;
- population size estimation
Modeling individual heterogeneity in capture probabilities has been one of the most challenging tasks in capture–recapture studies. Heterogeneity in capture probabilities can be modeled as a function of individual covariates, but correlation structure among capture occasions should be taking into account. A proposed generalized estimating equations (GEE) and generalized linear mixed modeling (GLMM) approaches can be used to estimate capture probabilities and population size for capture–recapture closed population models. An example is used for an illustrative application and for comparison with currently used methodology. A simulation study is also conducted to show the performance of the estimation procedures. Our simulation results show that the proposed quasi-likelihood based on GEE approach provides lower SE than partial likelihood based on either generalized linear models (GLM) or GLMM approaches for estimating population size in a closed capture–recapture experiment. Estimator performance is good if a large proportion of individuals are captured. For cases where only a small proportion of individuals are captured, the estimates become unstable, but the GEE approach outperforms the other methods.