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Aczel, Balazs; Szaszi, Barnabas; Nilsonne, Gustav; Akker, Olmo R. van den; Albers, Casper J.; Alm van Assen, Marcel; Bastiaansen, Jojanneke A.; Benjamin, Daniel; Boehm, Udo; Botvinik-Nezer, Rotem; Bringmann, Laura F.; Busch, Niko A.; Caruyer, Emmanuel; Cataldo, Andrea M.; Cowan, Nelson; Delios, Andrew; Dongen, Noah N. N. van; Donkin, Chris; Doorn, Johnny B. van; Dreber, Anna; Dutilh, Gilles; Egan, Gary F.; Gernsbacher, Morton Ann; Hoekstra, Rink; Hoffmann, Sabine; Holzmeister, Felix; Huber, Jürgen; Johannesson, Magnus; Jonas, Kai J.; Kindel, Alexander T.; Kirchler, Michael; Kunkels, Yoram K.; Lindsay, D. Stephen; Mangin, Jean-Francois; Matzke, Dora; Munafo, Marcus R.; Newell, Ben R.; Nosek, Brian A.; Poldrack, Russell A.; Ravenzwaaij, Don van; Rieskamp, Jorg; Salganik, Matthew J.; Sarafoglou, Alexandra; Schonberg, Tom; Schweinsberg, Martin; Shanks, David; Silberzahn, Raphael; Simons, Daniel J.; Spellman, Barbara A.; St.-Jean, Samuel; Starns, Jeffrey J.; Uhlmann, Eric Luis; Wicherts, Jelte and Wagenmakers, Eric-Jan (2021): Science Forum: Consensus-based guidance for conducting and reporting multi-analyst studies. In: eLife, Vol. 10, e72185 [PDF, 479kB]

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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