Abstract

In two-level designs, the total sample is a function of both the number of Level 2 clusters and the average number of Level 1 units per cluster. Traditional multilevel power calculations rely on either the arithmetic average or the harmonic mean when estimating the average number of Level 1 units across clusters of unbalanced size. The current study compares these two approaches with simulation-based power estimates in cluster randomized controlled trial designs with unbalanced cluster size. Results from the Monte Carlo study demonstrated that the largest differences in simulated and calculated power occurred in study designs with large variability in the number of Level 1 units sampled. We discuss implications of these findings for the design of cluster randomized trials.

摘要

在两水平设计中，总样本是水平 2 聚类数和每个聚类的平均水平 1 单位数的函数。传统的多级功率计算依赖于算术平均值或调和平均值，在估计不平衡大小的集群中的 1 级单元的平均数量时。目前的研究将这两种方法与集群随机对照试验设计中基于模拟的功率估计进行比较，其中集群大小不平衡。Monte Carlo 研究的结果表明，模拟功效和计算功效的最大差异发生在研究设计中，其中 1 级抽样单位数量的变异性很大。我们讨论了这些发现对整群随机试验设计的影响。