Statistical power and sample size requirements for three level hierarchical cluster randomized trials

Moonseong Heo, Andrew C. Leon

Research output: Contribution to journalArticle

48 Scopus citations

Abstract

Cluster randomized clinical trials (cluster-RCT), where the community entities serve as clusters, often yield data with three hierarchy levels. For example, interventions are randomly assigned to the clusters (level three unit). Health care professionals (level two unit) within the same cluster are trained with the randomly assigned intervention to provide care to subjects (level one unit). In this study, we derived a closed form power function and formulae for sample size determination required to detect an intervention effect on outcomes at the subject's level. In doing so, we used a test statistic based on maximum likelihood estimates from a mixed-effects linear regression model for three level data. A simulation study follows and verifies that theoretical power estimates based on the derived formulae are nearly identical to empirical estimates based on simulated data. Recommendations at the design stage of a cluster-RCT are discussed.

Original languageEnglish (US)
Pages (from-to)1256-1262
Number of pages7
JournalBiometrics
Volume64
Issue number4
DOIs
StatePublished - Dec 1 2008

Keywords

  • Effect size
  • Power
  • Sample size
  • Three level data

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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