School of Population & Public Health, University of British Columbia, 2206 East Mall, Vancouver, BC, V6T 1Z3, Canada.
Trials. 2019 Jun 17;20(1):360. doi: 10.1186/s13063-019-3471-8.
Health researchers are familiar with the concept of trial power, a number that prior to the start of a trial is intended to describe the probability that the results of the trial will correctly conclude that the intervention has an effect. Trial power, as calculated using standard software, is an expected power that arises from averaging hypothetical trial results over all possible treatment allocations that could be generated by the randomization algorithm. However, in the trial that ultimately is conducted, only one treatment allocation will occur, and the corresponding attained power (conditional on the allocation that occurred) is not guaranteed to be equal to the expected power and may be substantially lower. We provide examples illustrating this issue, discuss some circumstances when this issue is a concern, define and advocate the examination of the pre-randomization power distribution for evaluating the risk of obtaining unacceptably low attained power, and suggest the use of randomization restrictions to reduce this risk. In trials that randomize only a modest number of units, we recommend that trial designers evaluate the risk of getting low attained power and, if warranted, modify the randomization algorithm to reduce this risk.
健康研究人员熟悉试验功效的概念,这是一个在试验开始前用于描述试验结果正确推断干预措施有效果的概率的数值。使用标准软件计算的试验功效是一种期望功效,它源于通过随机化算法可能生成的所有可能治疗分配的假设性试验结果的平均值。然而,在最终进行的试验中,只会出现一种治疗分配,并且相应的获得功效(在出现的分配条件下)不一定等于期望功效,并且可能大大降低。我们提供了一些示例来说明这个问题,讨论了一些情况下这个问题需要关注的情况,定义并倡导检查预随机化功效分布,以评估获得不可接受的低获得功效的风险,并建议使用随机化限制来降低这种风险。在仅随机分配少量单位的试验中,我们建议试验设计者评估获得低功效的风险,如果有必要,修改随机化算法以降低这种风险。