ANOVA FOR LONGITUDINAL DATA WITH MISSING VALUES

• 成果类型: Article
• 署名作者: Chen, Song Xi; Zhong, Ping-Shou
• 署名单位: Iowa State University; Peking University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/10-AOS824
• 发表日期: 2010
• 页码: 3630-3659
• 关键词: semiparametric regression-analysis; varying-coefficient model; Empirical Likelihood; bootstrap; tests

摘要

We carry out ANOVA comparisons of multiple treatments for longitudinal studies with missing values. The treatment effects are modeled semiparametrically via a partially linear regression which is flexible in quantifying the time effects of treatments. The empirical likelihood is employed to formulate model-robust nonparametric ANOVA tests for treatment effects with respect to covariates, the nonparametric time-effect functions and interactions between covariates and time. The proposed tests can be readily modified for a variety of data and model combinations, that encompasses parametric, semiparametric and nonparametric regression models; cross-sectional and longitudinal data, and with or without missing values.