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Regression analysis of overdispersed correlated count data with subject specific covariates
Author(s) -
SolisTrapala I. L.,
Farewell V. T.
Publication year - 2005
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2121
Subject(s) - covariate , count data , statistics , computer science , econometrics , regression analysis , subject (documents) , overdispersion , mathematics , poisson distribution , library science
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.