Lancaster EPrints

Regression analysis of overdispersed correlated count data with subject specic covariates

Solis-Trapala, Ivonne L. and Farewell, Vernon T. (2005) Regression analysis of overdispersed correlated count data with subject specic covariates. Statistics in Medicine, 24 (16). pp. 2557-2575. ISSN 1097-0258

Full text not available from this repository.

Abstract

A robust likelihood approach for the analysis of overdispersed correlated count data that takes into account cluster varying covariates is proposed. We emphasise two characteristics of the proposed method: That the correlation structure satises the constraints on the second moments and that the estimation of the correlation structure guarantees consistent estimates of the regression coecients. In addition we extend the mean specication to include within- and between-cluster eects. The method is illustrated through the analysis of data from two studies. In the rst study, cross-sectional count data from a randomised controlled trial are analysed to evaluate the ecacy of a communication skills training programme. The second study involves longitudinal count data which represent counts of damaged hand joints in patients with psoriatic arthritis. Motivated by this study, we generalize our model to accommodate for a subpopulation of patients who are not susceptible to the development of damaged hand joints.

Item Type: Journal Article
Journal or Publication Title: Statistics in Medicine
Uncontrolled Keywords: /dk/atira/pure/researchoutput/libraryofcongress/r1
Subjects: ?? GENERALIZED ESTIMATING EQUATIONS MARGINAL MODEL MULTIVARIATE NEGATIVE BINOMIAL MODEL OVERDISPERSED CORRELATED COUNT DATA SUBJECT SPECIFIC COVARIATESR MEDICINE (GENERAL) ??
Departments: Faculty of Health and Medicine > Medicine
ID Code: 26519
Deposited By: Dr Ivonne Solis-Trapala
Deposited On: 26 May 2009 16:23
Refereed?: Yes
Published?: Published
Last Modified: 29 Apr 2019 14:29
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/26519

Actions (login required)

View Item