Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.
Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK.
J Epidemiol Popul Health. 2024 Feb;72(1):202198. doi: 10.1016/j.jeph.2024.202198. Epub 2024 Feb 13.
Cluster randomized trials are an essential design in public health and medical research, when individual randomization is infeasible or undesirable for scientific or logistical reasons. However, the correlation among observations within clusters leads to a decrease in statistical power compared to an individually randomised trial with the same total sample size. This correlation - often quantified using the intra-cluster correlation coefficient - must be accounted for in the sample size calculation to ensure that the trial is adequately powered. In this paper, we first describe the principles of sample size calculation for parallel-arm CRTs, and explain how these calculations can be extended to CRTs with cross-over designs, with a baseline measurement and stepped-wedge designs. We introduce tools to guide researchers with their sample size calculation and discuss methods to inform the choice of the a priori estimate of the intra-cluster correlation coefficient for the calculation. We also include additional considerations with respect to anticipated attrition, a small number of clusters, and use of covariates in the randomisation process and in the analysis.
当由于科学或后勤原因个体随机化不可行或不理想时,整群随机试验是公共卫生和医学研究中的一种重要设计。然而,与具有相同总样本量的个体随机试验相比,簇内观察之间的相关性会导致统计功效降低。这种相关性 - 通常使用组内相关系数来量化 - 必须在样本量计算中加以考虑,以确保试验具有足够的功效。在本文中,我们首先描述了平行臂 CRT 的样本量计算原则,并解释了如何将这些计算扩展到具有交叉设计、基线测量和阶乘楔形设计的 CRT。我们引入了一些工具来指导研究人员进行样本量计算,并讨论了在计算中告知先验估计组内相关系数选择的方法。我们还讨论了与预期失访、少量簇以及在随机化过程中和分析中使用协变量有关的其他问题。