Pöhlmann Anna, Konietschke Frank
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Biometry and Clinical Epidemiology, Berlin, Germany.
Biom J. 2023 Dec;65(8):e2200081. doi: 10.1002/bimj.202200081. Epub 2023 Sep 4.
Sample size calculations for two (independent) samples are well established and applied in (pre-)clinical research. When planning several samples, which is common in, for example, preclinical studies, sample size planning tools based on analysis of variance methods are available. Since the underlying effect sizes of these methods are often hard to interpret and to provide for the sample size planning, we employ multiple contrast test procedures for sample size computations in both parametric (under normality assumption) and nonparametric designs using Steel-type tests. Since the exact distributions of the test statistics are unknown under the alternative and variance heterogeneity, we use approximate solutions. Furthermore, since no closed formula for the sample size is available, we use numerical approximations for their computation. Extensive simulation studies are finally conducted to assess the quality of the approximations. It turns out that the methods are accurate in the sense that the multiple contrast test procedures reach the target power to detect the alternative of interest with the sample size computed. The developed procedures are a valuable tool to plan (pre-)clinical trials with several samples and are easily accessible in publicly available software.
两个（独立）样本的样本量计算方法已经很成熟，并应用于临床前研究。在计划多个样本时（例如在临床前研究中很常见），基于方差分析方法的样本量规划工具是可用的。由于这些方法的潜在效应量通常难以解释且难以用于样本量规划，因此我们在参数设计（在正态性假设下）和非参数设计中使用Steel型检验的多重对比检验程序来进行样本量计算。由于在备择假设和方差不齐的情况下检验统计量的精确分布是未知的，我们使用近似解。此外，由于没有样本量的封闭公式，我们使用数值近似来进行计算。最后进行了广泛的模拟研究以评估近似值的质量。结果表明，这些方法是准确的，即多重对比检验程序能够以计算出的样本量达到检测感兴趣备择假设的目标功效。所开发的程序是计划多个样本的临床前试验的宝贵工具，并且可以在公开可用的软件中轻松获取。
