Ontology highlight
ABSTRACT:
SUBMITTER: Aczel B
PROVIDER: S-EPMC8626083 | biostudies-literature | 2021 Nov
REPOSITORIES: biostudies-literature
Aczel Balazs B Szaszi Barnabas B Nilsonne Gustav G van den Akker Olmo R OR Albers Casper J CJ van Assen Marcel Alm MA Bastiaansen Jojanneke A JA Benjamin Daniel D Boehm Udo U Botvinik-Nezer Rotem R Bringmann Laura F LF Busch Niko A NA Caruyer Emmanuel E Cataldo Andrea M AM Cowan Nelson N Delios Andrew A van Dongen Noah Nn NN Donkin Chris C van Doorn Johnny B JB Dreber Anna A Dutilh Gilles G Egan Gary F GF Gernsbacher Morton Ann MA Hoekstra Rink R Hoffmann Sabine S Holzmeister Felix F Huber Juergen J Johannesson Magnus M Jonas Kai J KJ Kindel Alexander T AT Kirchler Michael M Kunkels Yoram K YK Lindsay D Stephen DS Mangin Jean-Francois JF Matzke Dora D Munafò Marcus R MR Newell Ben R BR Nosek Brian A BA Poldrack Russell A RA van Ravenzwaaij Don D Rieskamp Jörg J Salganik Matthew J MJ Sarafoglou Alexandra A Schonberg Tom T Schweinsberg Martin M Shanks David D Silberzahn Raphael R Simons Daniel J DJ Spellman Barbara A BA St-Jean Samuel S Starns Jeffrey J JJ Uhlmann Eric Luis EL Wicherts Jelte J Wagenmakers Eric-Jan EJ
eLife 20211109
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 a ...[more]