A linear mixed-effects model with heterogeneity in the random-effects population
A linear mixed-effects model with heterogeneity in the random-effects population
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DOI：
10.2307/2291398
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发表时间：
1996-03-01
影响因子：
3.7
通讯作者：
Lesaffre, E
中科院分区：
文献类型：
--
作者：
Verbeke, G;Lesaffre, E
本文研究了线性混合效应模型中随机效应的正态性假设对其估计的影响。II表明，如果随机效应的分布是正态分布的有限混合，那么如果假设正态性，则随机效应可能被估计得很差，并且目前用于检查模型假设的适当性的方法是不健全的。此外，有人认为，检测混合成分的更好方法是在模型中建立这个假设，然后将拟合模型与高斯模型进行“比较”。所有这些都是通过两个实际例子来说明的。
This article investigates the impact of the normality assumption for random effects on their estimates in the linear mixed-effects model. II shows that if the distribution of random effects is a finite mixture of normal distributions, then the random effects may be badly estimated if normality is assumed, and the current methods for inspecting the appropriateness of the model assumptions are not sound. Further, it is argued that a better way to detect the components of the mixture is to build this assumption in the model and then ''compare'' the fitted model with the Gaussian model. All of this is illustrated on two practical examples.