Herawati, Netti and Nisa, Khoirin (2017) A ROBUST PROCEDURE FOR GEE MODEL. Far East Journal of Mathematical Sciences (FJMS), 102 (3). pp. 645-654. ISSN ISSN: 0972-0871

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Official URL: http://www.pphmj.com http://dx.doi.org/10.17654/MS...


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.

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: 04 Sep 2017 01:48
Last Modified: 04 Sep 2017 01:48
URI: http://repository.lppm.unila.ac.id/id/eprint/3838

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