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  5. Subjective evidence evaluation survey for many-analysts studies

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Article
en
2024

Subjective evidence evaluation survey for many-analysts studies

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en
2024
Vol 11 (7)
Vol. 11
DOI: 10.1098/rsos.240125

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John P A Ioannidis
John P A Ioannidis

Stanford University

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Alexandra Sarafoglou
Suzanne Hoogeveen
Don van den Bergh
+37 more

Abstract

Many-analysts studies explore how well an empirical claim withstands plausible alternative analyses of the same dataset by multiple, independent analysis teams. Conclusions from these studies typically rely on a single outcome metric (e.g. effect size) provided by each analysis team. Although informative about the range of plausible effects in a dataset, a single effect size from each team does not provide a complete, nuanced understanding of how analysis choices are related to the outcome. We used the Delphi consensus technique with input from 37 experts to develop an 18-item subjective evidence evaluation survey (SEES) to evaluate how each analysis team views the methodological appropriateness of the research design and the strength of evidence for the hypothesis. We illustrate the usefulness of the SEES in providing richer evidence assessment with pilot data from a previous many-analysts study.

How to cite this publication

Alexandra Sarafoglou, Suzanne Hoogeveen, Don van den Bergh, Balázs Aczél, Casper J. Albers, Tim Althoff, Rotem Botvinik‐Nezer, Niko A. Busch, Andrea M. Cataldo, Berna Devezer, Noah N. N. van Dongen, Anna Dreber, Eiko I. Fried, Rink Hoekstra, Sabine Hoffman, Felix Holzmeister, Jürgen Huber, Nick Huntington‐Klein, John P A Ioannidis, Magnus Johannesson, Michael Kirchler, Eric Loken, Jan-Francois Mangin, Dóra Matzke, Albert J. Menkveld, Gustav Nilsonne, Don van Ravenzwaaij, Martin Schweinsberg, Hannah Schulz-Kuempel, David R. Shanks, Daniel J. Simons, Barbara A. Spellman, Andrea H. Stoevenbelt, Barnabás Szászi, Darinka Trübutschek, Francis Tuerlinckx, Eric Luis Uhlmann, Wolf Vanpaemel, Jelte M. Wicherts, Eric‐Jan Wagenmakers (2024). Subjective evidence evaluation survey for many-analysts studies. , 11(7), DOI: https://doi.org/10.1098/rsos.240125.

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Publication Details

Type

Article

Year

2024

Authors

40

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1098/rsos.240125

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