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Variability in the analysis of a single neuroimaging dataset by many teams

Abstract:
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41586-020-2314-9

Authors


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Role:
Author
ORCID:
0000-0003-2669-1877
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Role:
Author
ORCID:
0000-0001-9606-0427
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Role:
Author
ORCID:
0000-0003-4049-1871
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Institution:
University of Oxford
Division:
MSD
Department:
Nuffield Department of Population Health
Role:
Author
ORCID:
0000-0002-5553-7249
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Institution:
University of Oxford
Division:
MSD
Department:
Women's & Reproductive Health
Role:
Author


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Funder identifier:
https://ror.org/029chgv08
Grant:
100309/Z/12/Z


Publisher:
Nature Research
Journal:
Nature More from this journal
Volume:
582
Issue:
7810
Pages:
84-88
Publication date:
2020-05-20
Acceptance date:
2020-04-07
DOI:
EISSN:
1476-4687
ISSN:
0028-0836
Pmid:
32483374


Language:
English
Subjects:
Pubs id:
1107754
Local pid:
pubs:1107754
Deposit date:
2020-07-06

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