HackerPapers

arXiv:1606.08199stat.AP

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

Guillaume Flandin, Karl J. Friston

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., 2015). 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., 2015) for parametric procedures.

arXiv comments
Journal reference
DOI
Subjects
stat.APApplications (Statistics) stat.MEMethodology (Statistics)

On Hacker News

Linked by 2 identifiable commenters in 2 comments across 1 thread, from Jul 2016 to Jul 2016.

Comments linking this paper, per year.

Discussed in comments1 thread

    • Fwiw there's a response to an earlier (preprint) version of that paper from some of the developers of the packages in question. Preprint version of the "Cluster failure" paper, from last year: http://arxiv.org/abs/1511.01863 Response: http://arxiv.org/abs/1606.08199

      _deliriumView on HNParent context

    • The paper has been rebutted by other researchers who argue that the original results hold: "This technical report revisits the analysis of family-wise error rates in statistical parametric mapping - using random field theory - reported in (Eklund et al., 2015). Contrary to the…

      UVDMASView on HNParent context

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.