Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, 27705, USA.
Lifetime Data Anal. 2022 Jan;28(1):40-67. doi: 10.1007/s10985-021-09538-0. Epub 2021 Oct 29.
Each cluster consists of multiple subunits from which outcome data are collected. In a subunit randomization trial, subunits are randomized into different intervention arms. Observations from subunits within each cluster tend to be positively correlated due to the shared common frailties, so that the outcome data from a subunit randomization trial have dependency between arms as well as within each arm. For subunit randomization trials with a survival endpoint, few methods have been proposed for sample size calculation showing the clear relationship between the joint survival distribution between subunits and the sample size, especially when the number of subunits from each cluster is variable. In this paper, we propose a closed form sample size formula for weighted rank test to compare the marginal survival distributions between intervention arms under subunit randomization, possibly with variable number of subunits among clusters. We conduct extensive simulations to evaluate the performance of our formula under various design settings, and demonstrate our sample size calculation method with some real clinical trials.
每个簇由多个亚单位组成，从中收集结果数据。在亚单位随机化试验中，亚单位被随机分配到不同的干预组。由于共同的脆弱性，每个簇内的亚单位的观察结果往往呈正相关，因此，来自亚单位随机化试验的结果数据在臂之间以及每个臂内都存在依赖性。对于生存终点的亚单位随机化试验，很少有方法被提出用于样本量计算，显示出亚单位之间联合生存分布与样本量之间的明确关系，特别是当每个簇的亚单位数量可变时。在本文中，我们提出了一种加权秩检验的闭式样本量公式，用于比较亚单位随机化下干预臂之间的边缘生存分布，可能在簇之间的亚单位数量上有所不同。我们进行了广泛的模拟，以评估我们的公式在各种设计设置下的性能，并通过一些真实的临床试验展示我们的样本量计算方法。
