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. 2019 Apr 8;15(4):e1006973. doi: 10.1371/journal.pcbi.1006973

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© 2019 Lebreton et al

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Fig 3 — Incentive mechanism and overconfidence (A) Incentive mechanism. In Experiment 2, for the payout-relevant trials a lottery L is randomly drawn in the 50–100% interval and compared to the confidence rating C. If L > C, the lottery is implemented. A wheel of fortune, with a L% chance of losing is displayed, and played out. Then, feedback informed participants whether the lottery resulted in a win or a loss. If C > L, a clock is displayed together with the message “Please wait”, followed by feedback which depended on the correctness of the initial choice. With this mechanism, participant can maximize their earning by reporting their confidence accurately and truthfully. (B) Overconfidence. Individual averaged calibration, as a function of Experiment 2 experimental conditions (with a similar color code as in Figs 1 and 2). Connected dots represent individual data points in the within-subject design. The error bar displayed on the side of the scatter plots indicate the sample mean ± sem.