An integrated population-averaged approach to the design, analysis and sample size determination of cluster-unit trials.
While the mixed model approach to cluster randomization trials is relatively well developed, there has been less attention given to the design and analysis of population-averaged models for randomized and non-randomized cluster trials. We provide novel implementations of familiar methods to meet these needs. A design strategy that selects matching control communities based upon propensity scores, a statistical analysis plan for dichotomous outcomes based upon generalized estimating equations (GEE) with a design-based working correlation matrix, and new sample size formulae are applied to a large non-randomized study to reduce underage drinking. The statistical power calculations, based upon Wald tests for summary statistics, are special cases of a general power method for GEE.
Preisser
John S
JS
Department of Biostatistics, University of North Carolina School of Public Health, Chapel Hill, North Carolina 27599-7420, USA. jpreisse@bios.unc.edu
Young
Mary L
ML
Zaccaro
Daniel J
DJ
Wolfson
Mark
M
D000293:Adolescent; D000328:Adult; D000428:Alcohol Drinking / Q000517:prevention & control; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000706:statistics & numerical data*; D016896:Treatment Outcome; D014481:United States