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ANOVA for longitudinal data with missing values. (English) Zbl 1204.62124

Summary: 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 encompass parametric, semiparametric and nonparametric regression models; cross-sectional and longitudinal data, and with or without missing values.

MSC:

62J10 Analysis of variance and covariance (ANOVA)
62G10 Nonparametric hypothesis testing
62G08 Nonparametric regression and quantile regression
62G20 Asymptotic properties of nonparametric inference
65C60 Computational problems in statistics (MSC2010)
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