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

机译:使用广义估计方程和混合效应方法估计捕获概率

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摘要

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.
机译:在捕获概率中对个体异质性进行建模一直是捕获-捕获研究中最具挑战性的任务之一。可以将捕获概率的异质性建模为各个协变量的函数,但是应考虑捕获时机之间的相关结构。提出的广义估计方程(GEE)和广义线性混合建模(GLMM)方法可用于估计捕获再捕获封闭种群模型的捕获概率和种群大小。一个示例用于说明性应用,并用于与当前使用的方法进行比较。还进行了仿真研究,以显示估算程序的性能。我们的仿真结果表明,在封闭的捕获-捕获实验中,基于GEE方法的拟似然性提供的SE比基于广义线性模型(GLM)或GLMM方法的部分似然性更低。如果捕获了大量个人,则估计器性能良好。对于仅捕获一小部分人的情况,估计值将变得不稳定,但是GEE方法优于其他方法。

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