Cunningham Tina D, Johnson Robert E
Graduate Program in Public Health, Eastern Virginia Medical School, Norfolk, VA, USA
Department of Biostatistics, School of Medicine, Vanderbilt University, Nashville, TN, USA.
Stat Methods Med Res. 2016 Apr;25(2):505-19. doi: 10.1177/0962280212460443. Epub 2012 Oct 14.
Experiments with multiple nested levels where randomization can take place at any level bring challenges to the computation of sample sizes. Formulas derived under simple single-level experiments must be adjusted using multiplicative factors or design effects. In this work, we take a unified approach to finding the design effects in terms of intracluster correlations and present formulas to compute sample sizes of different levels. Equal cluster sample sizes and homogeneous within cluster variances are assumed.
在具有多个嵌套层次且可在任何层次进行随机化的实验中,样本量的计算面临挑战。在简单单层次实验中推导的公式必须使用乘法因子或设计效应进行调整。在这项工作中,我们采用一种统一的方法,根据群内相关性来确定设计效应,并给出计算不同层次样本量的公式。假设群样本量相等且群内方差同质。