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The Confidence Database

Dobromir Rahnev, Kobe Desender, Alan Lee, William T. Adler, David Aguilar‐Lleyda, Başak Akdoğan, Polina Arbuzova, Lauren Y. Atlas, Fuat Balcı, Ji Won Bang, Indrit Bègue, Damian P. Birney, Timothy F. Brady, Joshua Calder-Travis, Andrey Chetverikov, Torin K. Clark, Karen Davranche, Rachel N. Denison, Troy C. Dildine, Kit S. Double, Yalçın Akın Duyan, Nathan Faivre, Kaitlyn M. Fallow, Elisa Filevich, Thibault Gajdos, Regan Gallagher, Vincent de Gardelle, Sabina Gherman, Nadia Haddara, Marine Hainguerlot, Tzu‐Yu Hsu, Xiao Hu, Iñaki Iturrate, Matt Jaquiery, Justin Kantner, Marcin Koculak, Mahiko Konishi, Christina Koß, Peter D. Kvam, Sze Chai Kwok, Maël Lebreton, Karolina M. Lempert, Chien Ming Lo, Liang Luo, Brian Maniscalco, Antonio Martı́n, Sébastien Massoni, Julian Matthews, Audrey Mazancieux, Daniel M. Merfeld, Denis O’Hora, Eleanor R. Palser, Borysław Paulewicz, Michael Pereira, Caroline Peters, Marios G. Philiastides, Gerit Pfuhl, Fernanda Prieto, Manuel Rausch, Samuel Recht, Gabriel Reyes, Marion Rouault, Jérôme Sackur, Saeedeh Sadeghi, Jason Samaha, Tricia X. F. Seow, Medha Shekhar, Maxine T. Sherman, Marta Siedlecka, Zuzanna Skóra, Chen Song, David Soto, Sai Sun, Jeroen J. A. van Boxtel, Shuo Wang, Christoph T. Weidemann, Gabriel Weindel, Michał Wierzchoń, Xinming Xu, Qun Ye, Jiwon Yeon, Futing Zou, Ariel Zylberberg

2020Nature Human Behaviour162 citationsDOIOpen Access PDF

Abstract

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at https://osf.io/s46pr/) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects.

Topics & Concepts

Confidence intervalComputer scienceDatabaseInformation retrievalStatisticsMathematicsResearch Data Management PracticesScientific Computing and Data ManagementData Quality and Management
The Confidence Database | Litcius