Lui K J
Department of Mathematical Sciences, San Diego State University, California 92182-0314.
Biometrics. 1994 Mar;50(1):232-6.
Assuming that all subject responses were independent, O'Brien and Fleming (1979, Biometrics 35, 549-556) proposed a simple and useful multiple testing procedure for clinical trials for comparing two treatments with dichotomous data. Differences in the methods of evaluating subject responses at each evaluation time, however, may induce an intraclass correlation among these responses used in calculating the O'Brien-Fleming multiple testing procedure. On the basis of Monte Carlo simulations, we note that even a small intraclass correlation among subject responses in the same analysis can substantially inflate the Type I error of the O'Brien-Fleming multiple testing procedure. Furthermore, this inflation generally increases as either the number of analyses or the underlying response probability increases. We also have demonstrated that if we were able to maintain a uniform medical test procedure between the two treatments for each analysis, the actual Type I error of the O'Brien-Fleming multiple testing procedure may conversely become conservative.
假设所有受试者的反应都是独立的，奥布赖恩和弗莱明（1979年，《生物统计学》35卷，549 - 556页）为采用二分数据比较两种治疗方法的临床试验提出了一种简单且有用的多重检验程序。然而，在每个评估时间评估受试者反应的方法差异，可能会在用于计算奥布赖恩 - 弗莱明多重检验程序的这些反应之间引发组内相关性。基于蒙特卡罗模拟，我们注意到，即使在同一分析中受试者反应之间存在很小的组内相关性，也会大幅夸大奥布赖恩 - 弗莱明多重检验程序的I型错误。此外，这种夸大通常会随着分析次数或潜在反应概率的增加而增加。我们还证明了，如果我们能够在每次分析中在两种治疗方法之间保持统一的医学检验程序，奥布赖恩 - 弗莱明多重检验程序的实际I型错误可能反而会变得保守。
