Department of Psychology, University of Frankfurt, Frankfurt am Main, Germany.
Psychophysiology. 2019 Jun;56(6):e13335. doi: 10.1111/psyp.13335. Epub 2019 Jan 18.
Cluster-based permutation tests are gaining an almost universal acceptance as inferential procedures in cognitive neuroscience. They elegantly handle the multiple comparisons problem in high-dimensional magnetoencephalographic and EEG data. Unfortunately, the power of this procedure comes hand in hand with the allure for unwarranted interpretations of the inferential output, the most prominent of which is the overestimation of the temporal, spatial, and frequency precision of statistical claims. This leads researchers to statements about the onset or offset of a certain effect that is not supported by the permutation test. In this article, we outline problems and common pitfalls of using and interpreting cluster-based permutation tests. We illustrate these with simulated data in order to promote a more intuitive understanding of the method. We hope that raising awareness about these issues will be beneficial to common scientific practices, while at the same time increasing the popularity of cluster-based permutation procedures.
基于聚类的置换检验作为认知神经科学中一种推理方法，几乎已被普遍接受。它们巧妙地解决了高维脑磁图和脑电图数据中的多重比较问题。不幸的是，这种方法的功效伴随着对推理结果进行不当解释的诱惑，其中最突出的是高估了统计结论的时间、空间和频率精度。这导致研究人员对某一效应的起始或结束做出不被置换检验支持的陈述。在本文中，我们概述了使用和解释基于聚类的置换检验时可能出现的问题和常见陷阱。我们使用模拟数据来说明这些问题，以促进对该方法的更直观理解。我们希望提高对这些问题的认识将有助于规范科学实践，同时提高基于聚类的置换程序的普及程度。
