Regression analysis of overdispersed correlated count data with subject specific covariates

• Published in: Statistics in medicine Vol. 24; no. 16; pp. 2557 - 2575
• Main Authors: Solis-Trapala, I. L., Farewell, V. T.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 30.08.2005; Wiley Subscription Services, Inc
• Subjects: Arthritis; Arthritis, Psoriatic - pathology; Cluster Analysis; Communication; Correlation analysis; Female; generalized estimating equations; Hand Deformities - pathology; Humans; Joint Diseases - pathology; Male; marginal model; Models, Statistical; Multivariate Analysis; multivariate negative binomial model; overdispersed correlated count data; Physician-Patient Relations; Randomized Controlled Trials as Topic - methods; Regression Analysis; subject specific covariates
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.2121

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 satisfies the constraints on the second moments and that the estimation of the correlation structure guarantees consistent estimates of the regression coefficients. In addition we extend the mean specification to include within‐ and between‐cluster effects. The method is illustrated through the analysis of data from two studies. In the first study, cross‐sectional count data from a randomised controlled trial are analysed to evaluate the efficacy 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. Copyright © 2005 John Wiley & Sons, Ltd.