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.

每个集群由多个子单元组成，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中。由于共享的共同弱点，来自每个集群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各组之间以及各组内部具有依赖性。对于具有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，以显示亚单位之间的联合生存分布与样本量之间的明确关系，尤其是当来自每个集群的亚单位数量是可变的时。在本文中，我们提出了一个用于加权秩检验的封闭式样本大小公式，以比较亚单位随机化下干预组之间的边际生存分布，可能在集群中亚单位数量可变。我们进行了广泛的模拟以评估我们的配方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了我们的样本量计算方法。