Lewsey J D
Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand.
Stat Med. 2004 Mar 30;23(6):897-905. doi: 10.1002/sim.1665.
Stratified randomized designs are popular in cluster randomized trials (CRTs) because they increase the chance of the intervention groups being well balanced in terms of identified prognostic factors at baseline and may increase statistical power. The objective of this paper is to assess the gains in power obtained by stratifying randomization by cluster size, when cluster size is associated with an important cluster level factor which is otherwise unaccounted for in data analysis. A simulation study was carried out using a CRT where UK general practices were the randomized units as a template. The results show that when cluster size is strongly associated with a cluster level factor which is predictive of outcome, the stratified randomized design has superior power results to the completely randomized design and that the superiority is related to the number of clusters.
分层随机设计在整群随机试验（CRT）中很常见，因为它们增加了干预组在基线时根据已确定的预后因素实现良好平衡的机会，并且可能提高统计效能。本文的目的是评估在整群大小与一个重要的整群水平因素相关联（而该因素在数据分析中否则未被考虑）时，通过按整群大小对随机化进行分层所获得的效能提升。使用以英国全科医疗作为随机单位的CRT作为模板进行了一项模拟研究。结果表明，当整群大小与一个可预测结局的整群水平因素密切相关时，分层随机设计比完全随机设计具有更优的效能结果，并且这种优越性与整群数量有关。
