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An integrated population‐averaged approach to the design, analysis and sample size determination of cluster‐unit trials
Author(s) -
Preisser John S.,
Young Mary L.,
Zaccaro Daniel J.,
Wolfson Mark
Publication year - 2003
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.1379
Subject(s) - generalized estimating equation , sample size determination , gee , statistical power , statistics , matching (statistics) , propensity score matching , cluster randomised controlled trial , cluster (spacecraft) , population , mathematics , research design , sample (material) , randomized controlled trial , econometrics , computer science , medicine , chemistry , surgery , environmental health , chromatography , programming language
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. Copyright © 2003 John Wiley & Sons, Ltd.