ANOVA FOR LONGITUDINAL DATA WITH MISSING VALUES

被引:9
作者
Chen, Song Xi [1 ,2 ]
Zhong, Ping-Shou [1 ]
机构
[1] Iowa State Univ, Dept Stat, Ames, IA 50011 USA
[2] Peking Univ, Ctr Stat Sci, Guanghua Sch Management, Beijing 100871, Peoples R China
关键词
Analysis of variance; empirical likelihood; kernel smoothing; missing at random; semiparametric model; treatment effects; SEMIPARAMETRIC REGRESSION-ANALYSIS; VARYING-COEFFICIENT MODEL; EMPIRICAL LIKELIHOOD; BOOTSTRAP; TESTS;
D O I
10.1214/10-AOS824
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
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.
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页码:3630 / 3659
页数:30
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