Bayesian methods of analysis for cluser randomised trials with count outcome data

Clark, Allan B. ORCID: and Bachmann, Max O. ORCID: (2010) Bayesian methods of analysis for cluser randomised trials with count outcome data. Statistics in Medicine, 29 (2). pp. 199-209. ISSN 1097-0258

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Bayesian approaches to inference in cluster randomized trials have been investigated for normally distributed and binary outcome measures. However, relatively little attention has been paid to outcome measures which are counts of events. We discuss an extension of previously published Bayesian hierarchical models to count data, which usually can be assumed to be distributed according to a Poisson distribution. We develop two models, one based on the traditional rate ratio, and one based on the rate difference which may often be more intuitively interpreted for clinical trials, and is needed for economic evaluation of interventions. We examine the relationship between the intracluster correlation coefficient (ICC) and the between-cluster variance for each of these two models. In practice, this allows one to use the previously published evidence on ICCs to derive an informative prior distribution which can then be used to increase the precision of the posterior distribution of the ICC. We demonstrate our models using a previously published trial assessing the effectiveness of an educational intervention and a prior distribution previously derived. We assess the robustness of the posterior distribution for effectiveness to departures from a normal distribution of the random effects.

Item Type: Article
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Depositing User: EPrints Services
Date Deposited: 25 Nov 2010 11:09
Last Modified: 22 Dec 2022 09:30
DOI: 10.1002/sim.3747

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