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.
Publié le : 2010-12-15
Classification:
Analysis of variance,
empirical likelihood,
kernel smoothing,
missing at random,
semiparametric model,
treatment effects,
62G10,
62G20,
62G09
@article{1291126968,
author = {Chen, Song Xi and Zhong, Ping-Shou},
title = {ANOVA for longitudinal data with missing values},
journal = {Ann. Statist.},
volume = {38},
number = {1},
year = {2010},
pages = { 3630-3659},
language = {en},
url = {http://dml.mathdoc.fr/item/1291126968}
}
Chen, Song Xi; Zhong, Ping-Shou. ANOVA for longitudinal data with missing values. Ann. Statist., Tome 38 (2010) no. 1, pp. 3630-3659. http://gdmltest.u-ga.fr/item/1291126968/