Modelling of Covariance Structures in Generalised Estimating Equations for Longitudinal Data

Ye, Huajun and Pan, Jianxin (2006) Modelling of Covariance Structures in Generalised Estimating Equations for Longitudinal Data. Biometrika, 93. pp. 927-941. ISSN 1749-9097

PDF Modelling_of_Covariance.pdf Restricted to Repository staff only Download (166kB)

Abstract

When used for modelling longitudinal data generalised estimating equations specify a working structure for the within-subject covariance matrices, aiming to produce efficient parameter estimators. However, misspecification of the working covariance structure may lead to a large loss of efficiency of the estimators of the mean parameters. In this paper we propose an approach for joint modelling of the mean and covariance structures of longitudinal data within the framework of generalised estimating equations. The resulting estimators for the mean and covariance parameters are shown to be consistent and asymptotically Normally distributed. Real data analysis and simulation studies show that the proposed approach yields efficient estimators for both the mean and covariance parameters.

Item Type:	Article
Uncontrolled Keywords:	Cholesky decomposition; Efficiency; Generalised estimating equations; Longitudinal data; Misspecification of covariance structure; Modelling of mean and covariance structures.
Subjects:	MSC 2010, the AMS's Mathematics Subject Classification > 62 Statistics
Depositing User:	Dr Peter Neal
Date Deposited:	10 Jan 2007
Last Modified:	20 Oct 2017 14:12
URI:	https://eprints.maths.manchester.ac.uk/id/eprint/236

Actions (login required)

View Item