A Linear Mixed-Effects Model With Heterogeneity in the Random-Effects Population
研究了线性混合效应模型中随机效应的正态性假设对估计的影响，发现若随机效应来自正态分布的有限混合，则假设正态会导致估计偏差，并提出在模型中纳入混合假设以检测成分的方法。
Abstract This article investigates the impact of the normality assumption for random effects on their estimates in the linear mixed-effects model. It 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.