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Data Sets

My early studies of decisions from experience, like most other studies at the time, focused on small samples of subjects.

For example, in Bereby-Meyer and Erev (1998) we run only 14 participants in each of the three experimental conditions. The common assumption was that since each participant makes many decisions (500 in that study), the data is large enough.

 

Later we realized that the many participants tend to select their favorite action after several trials, and repeat this choice in most other trials. Thus, it is easy to overfit these data sets. To address this difficulty, my recent research focuses on large data sets, and choice prediction competitions.

 

Below are links to some of these data sets and the papers that summarize them.
If you cannot find the data you are looking for, please email me
(erev@technion.ac.il),

I may be able to find it.

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       Erev, I. Ert, E. Roth, A. E., Haruvy, E., Herzog, S., Hau, R. Hertwig, R. Stewart, T., West, R. and Lebiere, C.  (2010a) "A choice prediction competition, for choices from experience and from description."  Journal of Behavioral Decision Making, 23, 15-47.

Link to the paper  |  Link to the data (1st competition)

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       Erev, I., Ert, E., Roth, A.E. (2010b). “A choice prediction competition for market entry games: An introduction.” Games, 1, 117-136.

Link to the paper  |  Link to the data (2nd competition)

 

       Ert, E., Erev, I., Roth, A.E. (2011). “A choice prediction competition for A Choice Prediction Competition for Social Preferences in Simple Distribution Games: An Introduction.” Games.

Link to the paper  |  Link to the data (3rd  competition)

 

       Plonsky, O., Teodorescu, K., Erev, I. (2015). Reliance on small samples, the wavy recency effect, and similarity-based reasoning.  Psychological review, 122(4), 621.

Link

 

       Erev, I., Ert, E. Plosky, O., Cohen, D., & Cohen O. (2017). From anomalies to forecasts: Toward a descriptive model of decisions under risk, under ambiguity, and from experience. Psychological review, 122(4), 621.

Link to the paper  |  Link to the data

 

       Cohen, D., Plonsky, O., & Erev, I. (2020). On the impact of experience on probability weighting in decisions under risk. Decision, 7(2), 153.

Link to the paper  |  Link to the data

 

       Yakobi, O., Cohen, D., Naveh, E., & Erev, I. (2020). Reliance on small samples and the value of taxing reckless behaviors. Judgement and Decision Making, 15(2).

Link to the paper  |  Link to the data

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       Erev, I., Ert, E., Plonsky, O., & Roth, Y. (2023). Contradictory deviations from maximization: Environment-specific Biases, or reflections of basic properties of human learning? Psychological review.

Link to the paper  |  Link to the data

 

       Bonder, T., Erev, I., Ludvig, E. A., & Roth, Y. (2023). The common origin of both oversimplified and overly complex decision rules. Journal of Behavioral Decision Making, e2321.

Link to the paper   |  Link to the data

 

       Plonsky, O., Apel, R., Ert, E., Tennenholtz, M., Bourgin, D., Peterson, J.C., Reichman, D., Griffiths, T.L., Russell, S.J., Carter, E.C. and Cavanagh, J.F., Erev, I. (2019). Predicting human decisions with behavioral theories and machine learning. 

Link to the paper  |  Link to the data

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