Abstract
Abstract In longitudinal studies, multiple measurements are taken on the same subject at different points in time. Thus, observations for the same subject are correlated. This paper proposes a robust procedure for estimating parameters of regression model when generalized estimating equation (GEE) applied to longitudinal data that contains outliers. The procedure is a combination of the iteratively reweighted least square (IRLS) and least trimmed square (LTS) methods and is called iteratively reweighted least trimmed square (IRLTS). We conducted a simulation study for gamma model and Poisson model using the proposed method, the result shows that our approach can provide a better result than the classical GEE.
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