Sample size calculation for cluster randomized trials

Citations

SCOPUS

2

초록

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. © 2014, Korean Society of Veterinary Clinics. All rights reserved.

키워드

Cluster designDesign effectNomogramSample size
제목
Sample size calculation for cluster randomized trials
저자
Pak, SonilOh, Taeho
DOI
10.17555/ksvc.2014.08.31.4.288
발행일
2014
유형
Article
저널명
한국임상수의학회지
31
4
페이지
288 ~ 292