Title |
Can a single model account for both risky choices and inter-temporal choices? Testing the assumptions underlying models of risky inter-temporal choice
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Published in |
Psychonomic Bulletin & Review, June 2017
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DOI | 10.3758/s13423-017-1330-8 |
Pubmed ID | |
Authors |
Ashley Luckman, Chris Donkin, Ben R. Newell |
Abstract |
There is growing interest in modelling how people make choices that involve both risks and delays, i.e., risky inter-temporal choices. We investigated an untested assumption underlying several proposed risky inter-temporal choice models: that pure risky choices and pure inter-temporal choices are special cases of risky inter-temporal choice. We tested this assumption by presenting a single group of participants with risky choices and inter-temporal choices. We then compared the performance of a model that is fit to both choice types simultaneously, with the performance of separate models fit to the risky choice and inter-temporal choice data. We find, using Bayesian model comparison, that the majority of participants are best fit by a single model that incorporates both risky and inter-temporal choices. This result supports the assumption that risky choices and inter-temporal choices may be special cases of risky inter-temporal choice. Our results also suggest that, under the conditions of our experiment, interpretation of monetary value is very similar in risky choices and inter-temporal choices. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 20% |
United Kingdom | 2 | 20% |
Australia | 1 | 10% |
Germany | 1 | 10% |
Unknown | 4 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 6 | 60% |
Members of the public | 3 | 30% |
Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 46 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 20% |
Student > Master | 8 | 17% |
Researcher | 5 | 11% |
Student > Postgraduate | 4 | 9% |
Student > Doctoral Student | 3 | 7% |
Other | 6 | 13% |
Unknown | 11 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 21 | 46% |
Decision Sciences | 2 | 4% |
Social Sciences | 2 | 4% |
Economics, Econometrics and Finance | 2 | 4% |
Agricultural and Biological Sciences | 1 | 2% |
Other | 3 | 7% |
Unknown | 15 | 33% |