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Analysis of family-wise error rates in statistical parametric mapping using random field theory.

Flandin, G; Friston, KJ; (2017) Analysis of family-wise error rates in statistical parametric mapping using random field theory. Hum Brain Mapp 10.1002/hbm.23839. (In press). Green open access

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Abstract

This technical report revisits the analysis of family-wise error rates in statistical parametric mapping-using random field theory-reported in (Eklund et al. []: arXiv 1511.01863). Contrary to the understandable spin that these sorts of analyses attract, a review of their results suggests that they endorse the use of parametric assumptions-and random field theory-in the analysis of functional neuroimaging data. We briefly rehearse the advantages parametric analyses offer over nonparametric alternatives and then unpack the implications of (Eklund et al. []: arXiv 1511.01863) for parametric procedures. Hum Brain Mapp, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Type: Article
Title: Analysis of family-wise error rates in statistical parametric mapping using random field theory.
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/hbm.23839
Publisher version: http://dx.doi.org/10.1002/hbm.23839
Language: English
Additional information: © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Keywords: Family-wise error rate, random field theory, statistical parametric mapping, topological inference
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: http://discovery.ucl.ac.uk/id/eprint/1506354
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