Vierron Emilie, Giraudeau Bruno
INSERM CIC 202, Université François Rabelais, Tours, CHRU de Tours, France.
Contemp Clin Trials. 2007 Jul;28(4):451-8. doi: 10.1016/j.cct.2006.11.003. Epub 2006 Nov 17.
In multicenter trials, data from the same center are more similar than those from different centers. These similarities induce a correlation between data, known as the center effect, which is assessed by the intraclass correlation coefficient (ICC). Here, we derive a sample size formula for continuous data that takes into account this center effect. Our analytical developments lead to an elementary formula different from the classical one by a (1-rho) factor, where rho is the ICC. This work allows for adjusting and reducing the sample size according to the magnitude of the center effect and leads to a better consistency in the conduct of multicenter randomized trials.
在多中心试验中，来自同一中心的数据比来自不同中心的数据更相似。这些相似性会导致数据之间产生一种相关性，即所谓的中心效应，可通过组内相关系数（ICC）进行评估。在此，我们推导出了一个考虑到这种中心效应的连续数据样本量公式。我们的分析推导得出了一个基本公式，该公式与经典公式的不同之处在于有一个(1 - ρ)因子，其中ρ为ICC。这项工作能够根据中心效应的大小调整并减少样本量，并使多中心随机试验的实施具有更好的一致性。
