Journal
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Volume 100, Issue 472, Pages 1176-1184Publisher
AMER STATISTICAL ASSOC
DOI: 10.1198/016214505000000277
Keywords
B-spline; estimating equation; generalized linear model; longitudinal data; robustness
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In this article we consider robust generalized estimating equations for the analysis of semiparametric generalized partial linear models (GPLMs) for longitudinal data or clustered data in general. We approximate the nonparametric function in the GPLM by a regression spline, and use bounded scores and leverage-based weights in the estimating equation to achieve robustness against outliers. We show that the regression spline approach avoids some of the intricacies associated with the profile-kernel method, and that robust estimation and inference can be carried out operationally as if a generalized linear model were used.
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