One of the most difficult and important decisions in power analysis involves specifying an effect size. Researchers frequently employ definitions of small, medium, and large that were proposed by Jacob Cohen. These definitions are problematic for two reasons. First, they are arbitrary, based on non-scientific criteria. Second, they are inconsistent, changing dramatically and illogically as a function of the statistical test a researcher plans to use (e.g., t-test versus regression). These problems may be unknown to many researchers, but they have a huge impact on power analyses. Estimates of the required n may be inappropriately doubled or cut in half. For power analyses to have any meaning, these definitions of effect size should be avoided.

中文翻译：

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避免 Cohen 的“小”、“中”和“大”进行功效分析

功效分析中最困难和最重要的决定之一涉及指定效应大小。研究人员经常采用雅各布·科恩 (Jacob Cohen) 提出的小型、中型和大型定义。由于两个原因，这些定义是有问题的。首先，它们是任意的，基于非科学标准。其次，它们是不一致的，随着研究人员计划使用的统计检验（例如，t 检验与回归）的不同，它们会发生显着且不合逻辑的变化。许多研究人员可能不知道这些问题，但它们对功效分析产生了巨大影响。对所需 n 的估计可能不恰当地加倍或减半。为了使功效分析具有任何意义，应避免这些效应量的定义。