Constrained S-estimators for linear mixed effects models with covariance components.
Constrained S-estimators for linear mixed effects models with covariance components.
复制标题
用于具有协方差分量的线性混合效应模型的约束 S 估计器。
DOI：
10.1002/sim.4169
复制
发表时间：
2011
影响因子：
2
通讯作者：
Vishnyakov,Mark
中科院分区：
文献类型：
--
作者：
Chervoneva,Inna;Vishnyakov,Mark
线性混合效应模型越来越多地用于分析生物和生物医学数据。当多元正态假设对于LME模型不充分时，稳健的估计方法比最大似然估计方法更可取。M-estimator以前被认为是LME模型的稳健估计，最近提出了一个约束S-estimator。此S-估计量不能直接应用于具有相关误差项的LME模型和具有相关维度的向量随机效应。因此，提出了一种修改，将约束S-估计量的应用扩展到具有相关维度的多变量响应的LME模型和纵向数据。此外，一个新的计算算法被开发用于计算约束S-估计。基于原始Tukey双权重和转换双权重的S-估计量的性能在一个小型模拟研究中进行评估，其中重复的多变量响应具有相关维度。所提出的方法被应用于联合分析三个胆固醇成分，高密度脂蛋白，低密度脂蛋白和甘油三酯重复测量。版权所有© 2011约翰威利父子有限公司.
Linear mixed effects (LME) models are increasingly used for analyses of biological and biomedical data. When the multivariate normal assumption is not adequate for an LME model, then a robust estimation approach is preferable to the maximum likelihood one. M‐estimators were considered before for robust estimation of the LME models, and recently a constrained S‐estimator was proposed. This S‐estimator cannot be applied directly to LME models with correlated error terms and vector random effects with correlated dimensions. Therefore, a modification is proposed, which extends application of the constrained S‐estimator to the LME models for multivariate responses with correlated dimensions and to longitudinal data. Also, a new computational algorithm is developed for computing constrained S‐estimators. Performance of the S‐estimators based on the original Tukey's biweight and translated biweight is evaluated in a small simulation study with repeated multivariate responses with correlated dimensions. The proposed methodology is applied to jointly analyze repeated measures on three cholesterol components, HDL, LDL, and triglycerides. Copyright © 2011 John Wiley & Sons, Ltd.