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Consensus-based guidance for conducting and reporting multi-analyst studies

Balazs Aczel 1 Barnabas Szaszi 1 Gustav Nilsonne 2 Olmo van den Akker 3 Casper Albers 4 Marcel Alm van Assen 3 Jojanneke Bastiaansen 4 Daniel Benjamin 5 Udo Boehm 6 Rotem Botvinik-Nezer 7 Laura Bringmann 4 Niko Busch 8 Emmanuel Caruyer 9 Andrea Cataldo 10 Nelson Cowan 11 Andrew Delios 12 Noah van Dongen 6 Chris Donkin 13 Johnny van Doorn 6 Ann Dreber 14 Gilles Dutilh 15 Gary Egan 16 Morton Ann Gernsbacher 17 Rink Hoekstra 4 Sabine Hoffmann 18 Felix Holzmeister 19 Juergen Huber 19 Magnus Johannesson 14 Kai Jonas 20 Alexander Kindel 21 Michael Kirchler 19 Yoram Kunkels 4 D Stephen Lindsay 22 Jean-Francois Mangin 23 Dora Matzke 6 Marcus Munafò 24 Ben Newell 13 Brian Nosek 25 Russell Poldrack 26 Don van Ravenzwaaij 4 Jörg Rieskamp 27 Matthew Salganik 21 Alexandra Sarafoglou 6 Tom Schonberg 28 Martin Schweinsberg 29 David Shanks 30 Raphael Silberzahn 31 Daniel Simons 32 Barbara Spellman 25 Samuel St-Jean 33 Jeffrey Starns 34 Eric Luis Uhlmann 35 Jelte Wicherts 3 Eric-Jan Wagenmakers 6
Abstract : Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.
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https://www.hal.inserm.fr/inserm-03431812
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Submitted on : Tuesday, November 16, 2021 - 10:35:27 PM
Last modification on : Saturday, November 20, 2021 - 3:43:37 AM

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Balazs Aczel, Barnabas Szaszi, Gustav Nilsonne, Olmo van den Akker, Casper Albers, et al.. Consensus-based guidance for conducting and reporting multi-analyst studies. eLife, eLife Sciences Publication, 2021, 10, pp.e72185. ⟨10.7554/eLife.72185⟩. ⟨inserm-03431812⟩

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