The principled control of false positives in neuroimaging
The principled control of false positives in neuroimaging
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DOI：
10.1093/scan/nsp053
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发表时间：
2009-12-01
影响因子：
4.2
通讯作者：
Miller, Michael B.
中科院分区：
文献类型：
--
作者：
Bennett, Craig M.;Wolford, George L.;Miller, Michael B.
在功能神经成像实验的过程中产生了令人难以置信的大量数据。数据量给了我们更高的时间和空间分辨率，用来评估我们的结果。它还造成了一个令人震惊的多重测试问题。已经创建了许多方法，以原则性的方式解决神经成像中的多重测试问题。这些方法限制了结果的家庭错误率(FWER)或错误发现率(FDR)。这些有原则的方法在文献中得到了很好的证实，并且众所周知，它们可以适当地限制整个大脑的假阳性数量。然而，少数论文仍然是每月发表的，使用的方法根据进行的测试数量进行了不正确的修正。这些后一种方法限制了假阳性的体素概率，并且在结果中不产生关于全局假阳性率的信息。在这篇评论中，我们支持一种有原则的方法来解决多重测试问题--对整个大脑的假阳性率施加适当的限制，为读者提供正确评估结果所需的信息。
An incredible amount of data is generated in the course of a functional neuroimaging experiment. The quantity of data gives us improved temporal and spatial resolution with which to evaluate our results. It also creates a staggering multiple testing problem. A number of methods have been created that address the multiple testing problem in neuroimaging in a principled fashion. These methods place limits on either the familywise error rate (FWER) or the false discovery rate (FDR) of the results. These principled approaches are well established in the literature and are known to properly limit the amount of false positives across the whole brain. However, a minority of papers are still published every month using methods that are improperly corrected for the number of tests conducted. These latter methods place limits on the voxelwise probability of a false positive and yield no information on the global rate of false positives in the results. In this commentary, we argue in favor of a principled approach to the multiple testing problem-one that places appropriate limits on the rate of false positives across the whole brain gives readers the information they need to properly evaluate the results.