Sample Size Calculation for Cluster Randomized Trials

임상시험의 표본크기 계산

  • Pak, Son-Il (College of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University) ;
  • Oh, Tae-Ho (College of Veterinary Medicine, Kyungpook National University)
  • 박선일 (강원대학교 수의과대학 및 동물의학종합연구소) ;
  • 오태호 (경북대학교 수의과대학)
  • Accepted : 2014.06.18
  • Published : 2014.08.31

Abstract

A critical assumption of the standard sample size calculation is that the response (outcome) for an individual patient is completely independent to that for any other patient. However, this assumption no longer holds when there is a lack of statistical independence across subjects seen in cluster randomized designs. In this setting, patients within a cluster are more likely to respond in a similar manner; patient outcomes may correlate strongly within clusters. Thus, direct use of standard sample size formulae for cluster design, ignoring the clustering effect, may result in sample size that are too small, resulting in a study that is under-powered for detecting the desired level of difference between groups. This paper revisit worked examples for sample size calculation provided in a previous paper using nomogram to easy to access. Then we present the concept of cluster design illustrated with worked examples, and introduce design effect that is a factor to inflate the standard sample size estimates.

Keywords

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