Measures of between-cluster variability in cluster randomized trials with binary outcomes.

Full Abstract

Cluster randomized trials (CRTs) are increasingly used to evaluate the effectiveness of health-care interventions. A key feature of CRTs is that the observations on individuals within clusters are correlated as a result of between-cluster variability. Sample size formulae exist which account for such correlations, but they make different assumptions regarding the between-cluster variability in the intervention arm of a trial, resulting in different sample size estimates. We explore the relationship for binary outcome data between two common measures of between-cluster variability: k, the coefficient of variation and rho, the intracluster correlation coefficient. We then assess how the assumptions of constant k or rho across treatment arms correspond to different assumptions about intervention effects. We assess implications for sample size estimation and present a simple solution to the problems outlined. (c) 2009 John Wiley & Sons, Ltd.

Author information

Author/s: Thomson, Andrew (A); Hayes, Richard (R); Cousens, Simon (S);

Affiliation: Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, U.K. andrew.thomson(-atsign-)mhra.gsi.gov.uk

Journal and publication information

Publication Type: Journal Article

Journal: Statistics in medicine (Stat Med), published in England. (Language: eng)

Reference: 2009-May; vol 28 (issue 12) : pp 1739-51

Dates: Created 2009/05/07; Completed 2009/07/01;

PMID: 19378266, status: MEDLINE (last retrieval date: 7/1/2009, IMS Date: 01 Jul 2009 00:00:00)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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