Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA.
Biometrics. 2023 Jun;79(2):1114-1118. doi: 10.1111/biom.13668. Epub 2022 Apr 25.
Hung et al. (2007) considered the problem of controlling the type I error rate for a primary and secondary endpoint in a clinical trial using a gatekeeping approach in which the secondary endpoint is tested only if the primary endpoint crosses its monitoring boundary. They considered a two-look trial and showed by simulation that the naive method of testing the secondary endpoint at full level α at the time the primary endpoint reaches statistical significance does not control the familywise error rate at level α. Tamhane et al. (2010) derived analytic expressions for familywise error rate and power and confirmed the inflated error rate of the naive approach. Nonetheless, many people mistakenly believe that the closure principle can be used to prove that the naive procedure controls the familywise error rate. The purpose of this note is to explain in greater detail why there is a problem with the naive approach and show that the degree of alpha inflation can be as high as that of unadjusted monitoring of a single endpoint.
洪等人（2007 年）考虑了在临床试验中使用门控方法控制主要和次要终点的 I 型错误率的问题，其中仅当主要终点越过其监测边界时才测试次要终点。他们考虑了两次观察试验，并通过模拟表明，在主要终点达到统计显著性时，在全水平 α 下测试次要终点的幼稚方法不能控制水平 α 的总体错误率。Tamhane 等人（2010 年）推导出了总体错误率和功效的解析表达式，并证实了幼稚方法的膨胀错误率。尽管如此，许多人错误地认为闭包原理可用于证明幼稚程序控制总体错误率。本注释的目的是更详细地解释为什么幼稚方法存在问题，并表明α膨胀的程度可以与单个终点的未调整监测一样高。
