Abstract
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.
Citation
Song Xi Chen. Ping-Shou Zhong. "ANOVA for longitudinal data with missing values." Ann. Statist. 38 (6) 3630 - 3659, December 2010. https://doi.org/10.1214/10-AOS824
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