Estimation of capture probabilities using generalized estimating equations and mixed effects approaches

Authors

  • Md. Abdus Salam Akanda,

    Corresponding author
    1. Department of Mathematics, Research Center in Mathematics and Applications, University of Évora, Évora, Portugal
    2. Department of Statistics, Biostatistics & Informatics, University of Dhaka, Dhaka, Bangladesh
    • Correspondence

      Md. Abdus Salam Akanda, Department of Mathematics, Research Center in Mathematics and Applications, University of Évora, 7000-671 Évora, Portugal.

      Tel: +351965155536; Fax: +351266745393;

      E-mail: akanda_du@yahoo.com

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  • Russell Alpizar-Jara

    1. Department of Mathematics, Research Center in Mathematics and Applications, University of Évora, Évora, Portugal
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Abstract

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.

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