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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-捕获研究中,对捕获概率中的个体异质性进行建模一直是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。提议的广义估计方程(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。我们的模拟结果表明,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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