Lebreton J D, Choquet R, Gimenez O
CEFE, UMR 5175, CNRS, 1919 Route de Mende, 34293 Montpellier cedex 5, France.
Biometrics. 2012 Jun;68(2):494-503. doi: 10.1111/j.1541-0420.2011.01681.x. Epub 2011 Nov 14.
The need to consider in capture-recapture models random effects besides fixed effects such as those of environmental covariates has been widely recognized over the last years. However, formal approaches require involved likelihood integrations, and conceptual and technical difficulties have slowed down the spread of capture-recapture mixed models among biologists. In this article, we evaluate simple procedures to test for the effect of an environmental covariate on parameters such as time-varying survival probabilities in presence of a random effect corresponding to unexplained environmental variation. We show that the usual likelihood ratio test between fixed models is strongly biased, and tends to detect too often a covariate effect. Permutation and analysis of deviance tests are shown to behave properly and are recommended. Permutation tests are implemented in the latest version of program E-SURGE. Our approach also applies to generalized linear mixed models.
在过去几年中，人们已经广泛认识到，在捕获-再捕获模型中，除了诸如环境协变量等固定效应之外，还需要考虑随机效应。然而，正式的方法需要进行复杂的似然积分，概念和技术上的困难减缓了捕获-再捕获混合模型在生物学家中的传播。在本文中，我们评估了简单的程序，以测试环境协变量对参数（如存在对应于无法解释的环境变异的随机效应时的随时间变化的生存概率）的影响。我们表明，固定模型之间通常的似然比检验存在严重偏差，并且往往过于频繁地检测到协变量效应。结果表明，置换检验和离差分析检验表现良好，因此推荐使用。置换检验在程序E-SURGE的最新版本中实现。我们的方法也适用于广义线性混合模型。
