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Stat Med. 2009 May 30;28(12):1739-51. doi: 10.1002/sim.3582.

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

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Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, U.K.


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.

[Indexed for MEDLINE]

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