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Non-parametric combination and related permutation tests for neuroimaging

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Winkler, Anderson M., Webster, Matthew A., Brooks, Jonathan C., Tracey, Irene, Smith, Stephen M. and Nichols, Thomas E. (2016) Non-parametric combination and related permutation tests for neuroimaging. Human Brain Mapping, 37 (4). pp. 1486-1511. doi:10.1002/hbm.23115 ISSN 1065-9471.

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Official URL: http://dx.doi.org/10.1002/hbm.23115

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Abstract

In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well-known definition of union-intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume-based representations of the brain, including non-imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non-parametric combination (NPC) methodology, such that instead of a two-phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one-way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction.

Item Type: Journal Article
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Science, Engineering and Medicine > Science > Statistics
Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Imaging systems in medicine, Testing, Permutations
Journal or Publication Title: Human Brain Mapping
Publisher: John Wiley and Sons
ISSN: 1065-9471
Official Date: April 2016
Dates:
DateEvent
April 2016Published
5 February 2016Available
3 January 2016Accepted
5 August 2015Submitted
Volume: 37
Number: 4
Number of Pages: 26
Page Range: pp. 1486-1511
DOI: 10.1002/hbm.23115
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 5 February 2016
Date of first compliant Open Access: 5 February 2016
Funder: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Medical Research Council (Great Britain) (MRC), National Institutes of Health (U.S.) (NIH), Wellcome Trust (London, England), Marie Curie Initial Training Networks (ITN), GlaxoSmithKline, Dr Hadwen Trust, Barrow Neurological Institute
Grant number: 211534/2013-7 (CNPq), G0900908 (MRC), R01 EB015611-01 (NIH), NS41287 (NIH), 100309/Z/12/Z (NIH), 098369/Z/12/Z (NIH), MC-ITN-238593 (ITN)

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