Improper analysis of trials randomised using stratified blocks or minimisation
Improper analysis of trials randomised using stratified blocks or minimisation
复制标题
DOI：
10.1002/sim.4431
复制
发表时间：
2012-02-20
影响因子：
2
通讯作者：
Morris, Tim P.
中科院分区：
文献类型：
--
作者：
Kahan, Brennan C.;Morris, Tim P.
许多临床试验使用分层区组或最小化来限制随机化，以平衡治疗组间的预后因素。在统计学文献中广泛承认，后续分析应反映研究设计，并且应在分析中调整任何分层或最小化变量。然而，对最近的一般医学文献的回顾显示，41项合格研究中只有14项报告调整了分层或最小化变量的主要分析。我们表明，使用分层平衡治疗组导致治疗组之间的相关性。如果忽略这种相关性并进行未调整的分析，则治疗效果的标准误将向上偏倚，导致95%置信区间太宽，I类错误率太低，功效降低。相反，调整后的分析将给出有效的推断。我们通过模拟连续、二元和至事件发生时间的结局来探讨这一问题的程度，其中使用分层区组随机化或最小化分配治疗。版权所有（C）2011约翰威利父子有限公司
Many clinical trials restrict randomisation using stratified blocks or minimisation to balance prognostic factors across treatment groups. It is widely acknowledged in the statistical literature that the subsequent analysis should reflect the design of the study, and any stratification or minimisation variables should be adjusted for in the analysis. However, a review of recent general medical literature showed only 14 of 41 eligible studies reported adjusting their primary analysis for stratification or minimisation variables. We show that balancing treatment groups using stratification leads to correlation between the treatment groups. If this correlation is ignored and an unadjusted analysis is performed, standard errors for the treatment effect will be biased upwards, resulting in 95% confidence intervals that are too wide, type I error rates that are too low and a reduction in power. Conversely, an adjusted analysis will give valid inference. We explore the extent of this issue using simulation for continuous, binary and time-to-event outcomes where treatment is allocated using stratified block randomisation or minimisation. Copyright (C) 2011 John Wiley & Sons, Ltd.