MRC Clinical Trials Unit, University College London, London, UK.
Centre for Primary Care and Public Health, Queen Mary University of London, London, UK.
Stat Med. 2021 Nov 10;40(25):5474-5486. doi: 10.1002/sim.9135. Epub 2021 Jul 27.
There are sometimes cost, scientific, or logistical reasons to allocate individuals unequally in an individually randomized trial. In cluster randomized trials we can allocate clusters unequally and/or allow different cluster size between trial arms. We consider parallel group designs with a continuous outcome, and optimal designs that require the smallest number of individuals to be measured given the number of clusters. Previous authors have derived the optimal allocation ratio for clusters under different variance and/or intracluster correlations (ICCs) between arms, allowing different but prespecified cluster sizes by arm. We derive closed-form expressions to identify the optimal proportions of clusters and of individuals measured for each arm, thereby defining optimal cluster sizes, when cluster size can be chosen freely. When ICCs differ between arms but the variance is equal, the optimal design allocates more than half the clusters to the arm with the higher ICC, but (typically only slightly) less than half the individuals and hence a smaller cluster size. We also describe optimal design under constraints on the number of clusters or cluster size in one or both arms. This methodology allows trialists to consider a range for the number of clusters in the trial and for each to identify the optimal design. Except if there is clear prior evidence for the ICC and variance by arm, a range of values will need to be considered. Researchers should choose a design with adequate power across the range, while also keeping enough clusters in each arm to permit the intended analysis method.
在个体随机试验中,出于成本、科学或逻辑原因,有时需要不平等地分配个体。在整群随机试验中,我们可以不平等地分配整群,或者允许试验组之间的簇大小不同。我们考虑具有连续结果的平行组设计,以及在给定簇数量的情况下需要测量的个体数量最少的最优设计。以前的作者已经为不同方差和/或臂之间的组内相关系数(ICC)下的簇导出了最优分配比例,允许臂之间具有不同但预先指定的簇大小。我们推导出封闭形式的表达式来确定每个臂的最佳簇比例和要测量的个体比例,从而定义最佳簇大小,此时可以自由选择簇大小。当臂之间的 ICC 不同但方差相等时,最优设计将超过一半的簇分配给 ICC 较高的臂,但(通常只是略少)分配给个体的比例较小,因此簇的大小也较小。我们还描述了在一个或两个臂的簇数或簇大小的约束下的最优设计。这种方法允许试验人员考虑试验中簇的数量范围,并为每个范围确定最优设计。除非臂的 ICC 和方差有明确的先验证据,否则需要考虑一系列值。研究人员应在整个范围内选择具有足够功效的设计,同时在每个臂中保留足够的簇,以允许进行预期的分析方法。