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Measures of between‐cluster variability in cluster randomized trials with binary outcomes
Author(s) -
Thomson Andrew,
Hayes Richard,
Cousens Simon
Publication year - 2009
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.3582
Subject(s) - crts , cluster (spacecraft) , sample size determination , statistics , sample (material) , cluster randomised controlled trial , binary number , randomized controlled trial , econometrics , psychological intervention , mathematics , computer science , psychology , medicine , physics , computer graphics (images) , surgery , arithmetic , psychiatry , thermodynamics , programming language
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 ρ, the intracluster correlation coefficient. We then assess how the assumptions of constant k or ρ 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. Copyright © 2009 John Wiley & Sons, Ltd.