Sample size estimation in cluster randomized trials: An evidence-based perspective
AbstractThe evidence-based perspective to sample size estimation determines appropriate trial size by examining its potential impact on the literature. This approach is extended to determine the appropriate size of a planned cluster randomized trial by considering the role of the planned trial on a future meta-analysis (including current literature and the proposed study). A simulation-based algorithm allows consideration of variable cluster sizes and intracluster correlation coefficient values in conjunction with three approaches to sample size estimation, namely the power-based, variance reduction and non-inferiority perspectives. Two examples employing the sample size estimation techniques described are discussed in detail, while appropriate code is provided in the accompanying R package CRTSize.
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 56 (2012)
Issue (Month): 5 ()
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Web page: http://www.elsevier.com/locate/csda
Sample size estimation; Cluster randomized trials; Intracluster correlation coefficient; Meta-analysis; Design of experiments; Sequential methods;
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