2026-06-27T10:17:58Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/1008282025-03-18T12:34:16Zcom_20.500.14352_14col_20.500.14352_15
Botvinik-Nezer, R.
Holzmeister, F.
Camerer, C. F.
Dreber, A.
Huber, J.
Johannesson, M.
Kirchler, M.
Iwanir, R.
Mumford, J. A.
Adcock, R. A.
Avesani, P.
Baczkowski, B. M.
Bajracharya, A.
Bakst, L.
Ball, S.
Barilari, M.
Bault, N.
Beaton, D.
Beitner, J.
Benoit, R. G.
Berkers, R. M. W. J.
Bhanji, J. P.
Biswal, B. B.
Bobadilla-Suarez, S.
Bortolini, T.
Bottenhorn, K. L.
Bowring, A.
Braem, S.
Brooks, H. R.
Brudner, E. G.
Calderon, C. B.
Camilleri, J. A.
Castrellon, J. J.
Cecchetti, L.
Cieslik, E. C.
Cole, Z. J.
Collignon, O.
Cox, R. W.
Cunningham, W. A.
Czoschke, S.
Dadi, K.
Davis, C. P.
Luca, A. D.
Delgado, M. R.
Demetriou, L.
Dennison, J. B.
Di, X.
Dickie, E. W.
Dobryakova, E.
Donnat, C. L.
Dukart, J.
Duncan, N. W.
Durnez, J.
Eed, A.
Eickhoff, S. B.
Erhart, A.
Fontanesi, L.
Fricke, G. M.
Fu, S.
Galván, A.
Gau, R.
Genon, S.
Glatard, T.
Glerean, E.
Goeman, J. J.
Golowin, S. A. E.
González-García, C.
Gorgolewski, K. J.
Grady, C. L.
Green, M. A.
Guassi Moreira, J. F.
Guest, O.
Hakimi, S.
Hamilton, J. P.
Hancock, R.
Handjaras, G.
Harry, B.B.
Hawco, C.
Herholz, P.
Herman, G.
Heunis, S.
Hoffstaedter, F.
Hogeveen, J.
Holmes, S.
Hu, C. P.
Huettel, S. A.
Hughes, M. E.
Iacovella, V.
Iordan, A. D.
Isager, P. M.
Isik, A. I.
Jahn, Andrew
Johnson, Matthew R.
Johnstone, Tom
Joseph, Michael J. E.
Juliano, Anthony C.
Kable, Joseph W.
Kassinopoulos, Michalis
Koba, Cemal
Kong, Xiang-Zhen
Koscik, Timothy R.
Kucukboyaci, Nuri Erkut
Kuhl, Brice A.
Kupek, Sebastian
Laird, Angela R.
Lamm, Claus
Langner, Robert
Lauharatanahirun, Nina
Lee, Hongmi
Lee, Sangil
Leemans, Alexander
Leo, Andrea
Lesage, Elise
Li, Flora
Li, Monica Y. C.
Lim, Cheng Phui
Lintz, Evan N.
Liphardt, Schuyler W.
Losecaat Vermeer, Annabel B.
Love, Bradley C.
Mack, Michael L.
Malpica, Norberto
Marins, Theo
Maumet, Camille
McDonald, Kelsey
McGuire, Joseph T.
Méndez Leal, Adriana S.
Meyer, Benjamin
Meyer, Kristin N.
Mihai, Glad
Mitsis, Georgios D.
Moll, Jorge
Nielson, Dylan M.
Nilsonne, Gustav
Notter, Michael P.
Olivetti, Emanuele
Onicas, Adrian I.
Papale, Paolo
Patil, Kaustubh R.
Peelle, Jonathan E.
Pérez, Alexandre
Pischedda, Doris
Poline, Jean-Baptiste
Prystauka,Yanina
Ray, Shruti
Reuter-Lorenz, Patricia A.
Reynolds, Richard C.
Ricciardi, Emiliano
Rieck, Jenny R.
Rodriguez-Thompson, Anais M.
Romyn, Anthony
Salo, Taylor
Samanez-Larkin, Gregory R.
Sanz-Morales, Emilio
Schlichting, Margaret L.
Schultz, Douglas H.
Shen, Qiang
Sheridan, Margaret A.
Silvers, Jennifer A.
Skagerlund, Kenny
Smith, Alec
Smith, David V.
Sokol-Hessner, Peter
Steinkamp, Simon R.
Tashjian, Sarah M.
Thirion, Bertrand
Thorp, John N.
Tinghög, Gustav
Tisdall, Loreen
Tompson, Steven H.
Toro-Serey, Claudio
Torre Tresols, Juan Jesus
Tozzi, Leonardo
Truong, Vuong
Turella, Luca
van ‘t Veer, Anna E.
Verguts, Tom
Vettel, Jean M.
Vijayarajah, Sagana
Vo, Khoi
Wall, Matthew B.
Weeda, Wouter D.
Weis, Susanne
White, David J.
Wisniewski, David
Xifra-Porxas, Alba
Yearling, Emily A.
Yoon, Sangsuk
Yuan, Rui
Yuen, Kenneth S. L.
Lei Zhang
Zhang, Xu
Zosky, Joshua E.
Thomas E. Nichols,
Poldrack, Rusell A.
Schonberg, Tom
Melero Carrasco, Helena
2024-02-09T10:47:32Z
2024-02-09T10:47:32Z
2020-05-20
0028-0836
1476-4687
10.1038/s41586-020-2314-9
https://hdl.handle.net/20.500.14352/100828
https://www.nature.com/articles/s41586-020-2314-9
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 hypotheses1. 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 dataset2–5. 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.
eng
open access
Variability in the analysis of a single neuroimaging dataset by many teams
journal article