Sample size re-estimation in cluster randomization trials

Stephen Lake, Erin Kammann, Neil Klar, Rebecca Betensky

Research output: Contribution to journalArticlepeer-review


Cluster randomization trials in which families are the unit of allocation are commonly adopted for the evaluation of disease prevention interventions. Sample size estimation for cluster randomization trials depends on parameters that quantify the variability within and between clusters and the variability in cluster size. Accurate advance estimates of these nuisance parameters may be difficult to obtain and misspecification may lead to an underpowered study. Since families are typically recruited over time, we propose using a portion of the data to estimate the nuisance parameters and to re-estimate sample size based on the estimates. This extends the standard internal pilot study methods to the setting of cluster randomization trials. The effect of this design on the power, significance level and sample size is analysed via simulation and is shown to provide a flexible and practical approach to cluster randomization trials.

Original languageEnglish (US)
Pages (from-to)1337-1350
Number of pages14
JournalStatistics in Medicine
Issue number10
StatePublished - May 30 2002


  • Cluster randomization
  • Group sequential trials
  • Internal pilot

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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