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Reply to BROWN AND BEHRMANN, COX ET AL., AND KESSLER ET AL.: Data and code sharing is the way forward for fMRI
Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
Department of Statistics, University of Warwick, UK; WMG, University of Warwick, UK.
Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.ORCID-id: 0000-0002-9091-4724
2017 (engelsk)Inngår i: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, s. 1-2Artikkel i tidsskrift, Letter (Annet vitenskapelig) Published
Abstract [en]

We are glad that our paper (1) has generated intense discussions in the fMRI field (2⇓–4), on how to analyze fMRI data, and how to correct for multiple comparisons. The goal of the paper was not to disparage any specific fMRI software, but to point out that parametric statistical methods are based on a number of assumptions that are not always valid for fMRI data, and that nonparametric statistical methods (5) are a good alternative. Through AFNI’s introduction of nonparametric statistics in the function 3dttest++ (3, 6), the three most common fMRI softwares now all support nonparametric group inference [SPM through the toolbox SnPM (www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/nichols/software/snpm), and FSL through the function randomise].

Cox et al. (3) correctly point out that the bug in the AFNI function 3dClustSim only had a minor impact on the false-positive rate (FPR). This was also covered in our original paper (1): “We note that FWE [familywise error] rates are lower with the bug-fixed 3dClustSim function. As an example, the updated function reduces the degree of false …

sted, utgiver, år, opplag, sider
2017. s. 1-2
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Identifikatorer
URN: urn:nbn:se:liu:diva-136541DOI: 10.1073/pnas.1620285114OAI: oai:DiVA.org:liu-136541DiVA, id: diva2:1089371
Tilgjengelig fra: 2017-04-19 Laget: 2017-04-19 Sist oppdatert: 2019-07-04bibliografisk kontrollert

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Reply to BROWN AND BEHRMANN, COX ET AL., AND KESSLER ET AL.: Data and code sharing is the way forward for fMRI(504 kB)122 nedlastinger
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