Department of Management Science, National Chiao Tung University, Hsinchu 30010, Taiwan, ROC.
Comput Methods Programs Biomed. 2016 Apr;126:110-7. doi: 10.1016/j.cmpb.2015.12.004. Epub 2015 Dec 24.
Equivalence testing is recommended as a better alternative to the traditional difference-based methods for demonstrating the comparability of two or more treatment effects. Although equivalent tests of two groups are widely discussed, the natural extensions for assessing equivalence between several groups have not been well examined. This article provides a detailed and schematic comparison of the ANOVA F and the studentized range tests for evaluating the comparability of several standardized effects. Power and sample size appraisals of the two grossly distinct approaches are conducted in terms of a constraint on the range of the standardized means when the standard deviation of the standardized means is fixed. Although neither method is uniformly more powerful, the studentized range test has a clear advantage in sample size requirements necessary to achieve a given power when the underlying effect configurations are close to the priori minimum difference for determining equivalence. For actual application of equivalence tests and advance planning of equivalence studies, both SAS and R computer codes are available as supplementary files to implement the calculations of critical values, p-values, power levels, and sample sizes.
等效检验被推荐为一种优于传统基于差异的方法,用于证明两种或多种治疗效果的可比性。尽管已经广泛讨论了两组等效检验,但尚未很好地检验评估几组之间等效性的自然扩展。本文详细比较了方差分析 F 检验和学生化极差检验,以评估几个标准化效果的可比性。在固定标准化均值标准差的情况下,通过标准化均值范围的约束,对两种截然不同方法的功效和样本量进行了评估。虽然这两种方法都不是普遍更有效,但在潜在效应接近确定等效性的先验最小差异时,学生化极差检验在实现给定功效所需的样本量方面具有明显优势。对于等效性检验的实际应用和等效性研究的预先规划,SAS 和 R 计算机代码都作为补充文件提供,以实现临界值、p 值、功效水平和样本量的计算。