The Ohio State University, Columbus, USA.
Queen's University, Kingston, Ontario, Canada.
Pers Soc Psychol Bull. 2022 Jul;48(7):1105-1117. doi: 10.1177/01461672211030811. Epub 2021 Jul 26.
Traditionally, statistical power was viewed as relevant to research planning but not evaluation of completed research. However, following discussions of high false finding rates (FFRs) associated with low statistical power, the assumed level of statistical power has become a key criterion for research acceptability. Yet, the links between power and false findings are not as straightforward as described. Assumptions underlying FFR calculations do not reflect research realities in personality and social psychology. Even granting the assumptions, the FFR calculations identify important limitations to any general influences of statistical power. Limits for statistical power in inflating false findings can also be illustrated through the use of FFR calculations to (a) update beliefs about the null or alternative hypothesis and (b) assess the relative support for the null versus alternative hypothesis when evaluating a set of studies. Taken together, statistical power should be de-emphasized in comparison to current uses in research evaluation.
传统上，统计功效被视为与研究计划相关，但与已完成的研究无关。然而，随着与低统计功效相关的高错误发现率（FFR）的讨论，假设的统计功效已成为研究可接受性的关键标准。然而，功效和错误发现之间的联系并不像描述的那样直接。FFR 计算的假设并不反映人格和社会心理学研究的实际情况。即使承认这些假设，FFR 计算也确定了统计功效对任何一般影响的重要限制。通过使用 FFR 计算来（a）更新对零假设或替代假设的信念，以及（b）在评估一组研究时评估零假设与替代假设的相对支持，也可以说明统计功效在夸大错误发现方面的局限性。总的来说，与当前在研究评估中的使用相比，统计功效应该被淡化。
