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

来源：

ANNALS OF STATISTICS | 2010年 / 38卷 / 06期

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.

引用

页码：3630 / 3659

页数：30

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