Herawati, Netti and Nisa, Khoirin A Robust Procedure for GEE Model. Far East Journal of Mathematical Sciences (FJMS). ISSN 0972-0871 (Submitted)

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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. 2010 Mathematics Subject Classification: 62J12. Keywords: longitudinal data, outlier, regression model.

Item Type:	Article
Subjects:	H Social Sciences > HA Statistics
Divisions:	Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Matematika
Depositing User:	Dr NETTI HERAWATI
Date Deposited:	07 Jun 2017 09:22
Last Modified:	07 Jun 2017 09:22
URI:	http://repository.lppm.unila.ac.id/id/eprint/2972

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