Nisa, Khoirin and Herawati, Netti (2017) Robust Estimation of Generalized Estimating Equation when Data Contain Outliers. INSIST, 2 (1). pp. 1-5. ISSN 2502-8588

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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.

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:	29 May 2017 06:38
Last Modified:	29 May 2017 06:38
URI:	http://repository.lppm.unila.ac.id/id/eprint/1835

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