Anisimov Vladimir V, Yeung Wai Y, Coad D Stephen
School of Mathematics and Statistics, University of Glasgow, 15 University Gardens, Glasgow, G12 8QW, U.K.
Roche Products Limited, 6 Falcon Way, Shire Park, Welwyn Garden City, AL7 1TW, U.K.
Stat Med. 2017 Apr 15;36(8):1302-1318. doi: 10.1002/sim.7206. Epub 2016 Dec 27.
Randomisation schemes are rules that assign patients to treatments in a clinical trial. Many of these schemes have the common aim of maintaining balance in the numbers of patients across treatment groups. The properties of imbalance that have been investigated in the literature are based on two treatment groups. In this paper, their properties for K > 2 treatments are studied for two randomisation schemes: centre-stratified permuted-block and complete randomisation. For both randomisation schemes, analytical approaches are investigated assuming that the patient recruitment process follows a Poisson-gamma model. When the number of centres involved in a trial is large, the imbalance for both schemes is approximated by a multivariate normal distribution. The accuracy of the approximations is assessed by simulation. A test for treatment differences is also considered for normal responses, and numerical values for its power are presented for centre-stratified permuted-block randomisation. To speed up the calculations, a combined analytical/approximate approach is used. Copyright © 2016 John Wiley & Sons, Ltd.
随机化方案是在临床试验中将患者分配到治疗组的规则。这些方案中的许多都有一个共同目标，即保持各治疗组患者数量的平衡。文献中研究的不平衡特性是基于两个治疗组的。本文针对两种随机化方案研究了K>2种治疗时的特性：中心分层置换区组随机化和完全随机化。对于这两种随机化方案，在假设患者招募过程遵循泊松-伽马模型的情况下研究了分析方法。当试验涉及的中心数量很大时，两种方案的不平衡情况都可以用多元正态分布来近似。通过模拟评估近似的准确性。对于正态反应还考虑了治疗差异检验，并给出了中心分层置换区组随机化的检验效能数值。为了加快计算速度，采用了一种分析/近似相结合的方法。版权所有©2016约翰威立父子有限公司。
