Sample size for cluster randomized trials: effect of coefficient of variation of cluster size and analysis method
Sample size for cluster randomized trials: effect of coefficient of variation of cluster size and analysis method
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DOI：
10.1093/ije/dyl129
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发表时间：
2006-10-01
影响因子：
7.7
通讯作者：
Kerry, Sally
中科院分区：
文献类型：
--
作者：
Eldridge, Sandra M.;Ashby, Deborah;Kerry, Sally
背景随机分组试验越来越受欢迎。在许多这样的试验中，集群大小是不相等的。这可能会影响试验功效，但这些试验的标准样本量公式忽略了这一点。以前的研究解决这个问题主要集中在连续的结果或方法，有时很难在practice.Methods中使用，我们展示了如何使用一个简单的公式来判断不同类型的分析和连续和二进制的结果不平等的集群大小的可能影响。我们探讨了在这个公式中所需的聚类大小的变异系数的实际估计，并证明了一个假设的，但典型的试验随机英国general practices.Results简单的公式提供了一个很好的估计样本量的要求，使用聚类水平分析加权聚类大小和保守估计其他类型的分析试验分析。对于随机化英国全科实践的试验，聚类大小的变异系数取决于实践列表大小的变化、正在检查的医疗状况的发生率或患病率的变化以及实践和患者招募策略，并且对于许多试验，预计近似于0.65。个体水平的分析可以显着更有效的一些集群水平的analysis.Conclusions当变异系数< 0.23时，调整变量集群大小对样本量的影响可以忽略不计。大多数随机化英国全科实践的试验和许多其他集群随机化试验应在其样本量计算中考虑可变集群大小。
Background Cluster randomized trials are increasingly popular. In many of these trials, cluster sizes are unequal. This can affect trial power, but standard sample size formulae for these trials ignore this. Previous studies addressing this issue have mostly focused on continuous outcomes or methods that are sometimes difficult to use in practice.Methods We show how a simple formula can be used to judge the possible effect of unequal cluster sizes for various types of analyses and both continuous and binary outcomes. We explore the practical estimation of the coefficient of variation of cluster size required in this formula and demonstrate the formula's performance for a hypothetical but typical trial randomizing UK general practices.Results The simple formula provides a good estimate of sample size requirements for trials analysed using cluster-level analyses weighting by cluster size and a conservative estimate for other types of analyses. For trials randomizing UK general practices the coefficient of variation of cluster size depends on variation in practice list size, variation in incidence or prevalence of the medical condition under examination, and practice and patient recruitment strategies, and for many trials is expected to be similar to 0.65. Individual-level analyses can be noticeably more efficient than some cluster-level analyses in this context.Conclusions When the coefficient of variation is < 0.23, the effect of adjustment for variable cluster size on sample size is negligible. Most trials randomizing UK general practices and many other cluster randomized trials should account for variable cluster size in their sample size calculations.