Li Jianghao, Jung Sin-Ho
Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA.
Stat Med. 2020 Nov 10;39(25):3608-3623. doi: 10.1002/sim.8683. Epub 2020 Jul 30.
Cluster randomization trials randomize groups (called clusters) of subjects (called subunits) between intervention arms, and observations are collected from each subject. In this case, subunits within each cluster share common frailties, so that the observations from subunits of each cluster tend to be correlated. Oftentimes, the outcome of a cluster randomization trial is a time-to-event endpoint with censoring. In this article, we propose a closed form sample size formula for weighted rank tests to compare the marginal survival distributions between intervention arms under cluster randomization with possibly variable cluster sizes. Extensive simulation studies are conducted to evaluate the performance of our sample size formula under various design settings. Real study examples are taken to demonstrate our method.
整群随机试验将受试者组(称为整群)随机分配到各干预组,并且从每个受试者收集观察数据。在这种情况下,每个整群内的亚组具有共同的脆弱性,因此每个整群中亚组的观察结果往往具有相关性。通常,整群随机试验的结果是一个带有删失的事件发生时间终点。在本文中,我们提出了一个用于加权秩检验的封闭式样本量公式,以比较整群随机化下各干预组之间的边际生存分布,整群大小可能不同。我们进行了广泛的模拟研究,以评估我们的样本量公式在各种设计设置下的性能。通过实际研究实例来展示我们的方法。