Overall J E, Doyle S R
Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston 77225.
Control Clin Trials. 1994 Apr;15(2):100-23. doi: 10.1016/0197-2456(94)90015-9.
Formulas for estimating sample sizes that are required to provide specified power for analysis of variance (ANOVA) tests of significance in a two-group repeated measurements design are presented and evaluated. Power and sample size requirements depend on the pattern of treatment effects and the pattern of correlations among the repeated measurements, as well as on parameters common to sample size estimation for cross-sectional comparisons of treatment effects in simple randomized designs. Simplifying assumptions permit generation of these numerous parameter estimates from predictions of the magnitude of the standardized "effect size" at end of trial and the single correlation between the baseline and endpoint measurements. Monte Carlo methods are used to verify the actual power of different tests of significance for treatment effects in repeated measurement designs using sample sizes estimated by the formulas. The sample size implications of different patterns of treatment effects, levels of correlation, and numbers of repeated measurements are evaluated.
本文给出并评估了用于估计样本量的公式,这些公式用于在两组重复测量设计中为方差分析(ANOVA)显著性检验提供特定功效。功效和样本量要求取决于治疗效果模式、重复测量之间的相关性模式,以及简单随机设计中治疗效果横断面比较的样本量估计所共有的参数。简化假设允许根据试验结束时标准化“效应大小”的大小预测以及基线测量与终点测量之间的单一相关性来生成这些众多参数估计值。使用蒙特卡罗方法来验证在重复测量设计中使用公式估计的样本量对治疗效果进行不同显著性检验的实际功效。评估了不同治疗效果模式、相关水平和重复测量次数对样本量的影响。