Yafune Akifumi, Funatogawa Takashi, Ishiguro Makio
Clinic Sendagaya, Tokyo, Japan.
Stat Med. 2005 Nov 30;24(22):3417-29. doi: 10.1002/sim.2191.
In clinical data analysis, the restricted maximum likelihood (REML) method has been commonly used for estimating variance components in the linear mixed effects model. Under the REML estimation, however, it is not straightforward to compare several linear mixed effects models with different mean and covariance structures. In particular, few approaches have been proposed for the comparison of linear mixed effects models with different mean structures under the REML estimation. We propose an approach using extended information criterion (EIC), which is a bootstrap-based extension of AIC, for comparing linear mixed effects models with different mean and covariance structures under the REML estimation. We present simulation studies and applications to two actual clinical data sets.
在临床数据分析中，限制最大似然法（REML）已被广泛用于估计线性混合效应模型中的方差分量。然而，在REML估计下，比较具有不同均值和协方差结构的多个线性混合效应模型并非易事。特别是，在REML估计下，很少有方法被提出用于比较具有不同均值结构的线性混合效应模型。我们提出了一种使用扩展信息准则（EIC）的方法，它是AIC基于自助法的扩展，用于在REML估计下比较具有不同均值和协方差结构的线性混合效应模型。我们展示了模拟研究以及对两个实际临床数据集的应用。
