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All Journal INSIST (International Series on Interdisciplinary Research)
Netti Herawati
Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Lampung, Jalan Prof. Soemantri Brojonegoro No. 1, Bandar Lampung, Indonesia.
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Robust Estimation of Generalized Estimating Equation when Data Contain Outliers Khoirin Nisa; Netti Herawati
INSIST Vol 2, No 1 (2017)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (94.379 KB) | DOI: 10.23960/ins.v2i1.23

Abstract

Abstract—In this paper, a robust procedure for estimating parameters of regression model when generalized estimating equation (GEE) applied to longitudinal data that contains outliers is proposed. The method is called ‘iteratively reweighted least trimmed square’ (IRLTS) which is a combination of the iteratively reweighted least square (IRLS) and least trimmed square (LTS) methods. To assess the proposed method a simulation study was conducted and the result shows that the method is robust against outliers.Keywords—GEE, IRLS, LTS, longitudinal data, regression model.
Co-Authors Khoirin Nisa