The Confidence Database
Date
2020
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Article
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Abstract
Understanding how people rate their confidence is critical for characterizing 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 analyzed in multiple software packages. Each dataset is further accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (available at osf.io/s46pr) contained 145 datasets with data from over 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. We show the usefulness of this large collection of datasets in four different analyses that provide precise estimation for several foundational confidence-related effects.
Description
Karolina M. Lempert,; Chien Ming Lo; Liang Luo; Brian Maniscalco; Antonio Martin; 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; 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; and Ariel Zylberberg
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Citation
Nature Human Behaviour, 2020 Mar;4(3):317-325
Keywords
Confianza, Paradigma, Población, Base de datos, Datos