Tang Yongqiang
Tesaro, Department of Biometrics, 1000 Winter Street, Waltham, MA, USA.
Stat Med. 2020 Oct 30;39(24):3427-3457. doi: 10.1002/sim.8674. Epub 2020 Sep 9.
In a series of articles, Gart and Nam construct the efficient score tests and confidence intervals with or without skewness correction for stratified comparisons of binomial proportions on the risk difference, relative risk, and odds ratio effect metrics. However, the stratified score methods and their properties are not well understood. We rederive the efficient score tests, which reveals their theoretical relationship with the contrast-based score tests, and provides a basis for adapting the method by using other weighting schemes. The inverse variance weight is optimal for a common treatment effect in large samples. We explore the behavior of the score approach in the presence of extreme outcomes when either no or all subjects in some strata are responders, and provide guidance on the choice of weights in the analysis of rare events. The score method is recommended for studies with a small number of moderate or large sized strata. A general framework is proposed to calculate the asymptotic power and sample size for the score test in superiority, noninferiority and equivalence clinical trials, or case-control studies. We also describe a nearly exact procedure that underestimates the exact power, but the degree of underestimation can be controlled to a negligible level. The proposed methods are illustrated by numerical examples.
在一系列文章中，加特和纳姆构建了用于二项比例分层比较的有效得分检验和置信区间，这些检验和区间针对风险差、相对风险和比值比效应指标进行了有或无偏度校正的处理。然而，分层得分方法及其性质并未得到很好的理解。我们重新推导了有效得分检验，揭示了它们与基于对比的得分检验的理论关系，并为通过使用其他加权方案来调整该方法提供了依据。在大样本中，逆方差权重对于共同治疗效应是最优的。我们探讨了在某些层中没有受试者或所有受试者都是反应者这种极端结果情况下得分方法的行为，并为罕见事件分析中的权重选择提供指导。对于具有少量中等或大尺寸层的研究，推荐使用得分方法。提出了一个通用框架，用于计算优效性、非劣效性和等效性临床试验或病例对照研究中得分检验的渐近检验效能和样本量。我们还描述了一种几乎精确的程序，该程序会低估精确检验效能，但低估程度可控制到可忽略不计的水平。通过数值示例对所提出的方法进行了说明。
