Literature DB >> 27620961

How (in)variant are subjective representations of described and experienced risk and rewards?

David Kellen1, Thorsten Pachur2, Ralph Hertwig2.   

Abstract

Decisions under risk have been shown to differ depending on whether information on outcomes and probabilities is gleaned from symbolic descriptions or gathered through experience. To some extent, this description-experience gap is due to sampling error in experience-based choice. Analyses with cumulative prospect theory (CPT), investigating to what extent the gap is also driven by differences in people's subjective representations of outcome and probability information (taking into account sampling error), have produced mixed results. We improve on previous analyses of description-based and experience-based choices by taking advantage of both a within-subjects design and a hierarchical Bayesian implementation of CPT. This approach allows us to capture both the differences and the within-person stability of individuals' subjective representations across the two modes of learning about choice options. Relative to decisions from description, decisions from experience showed reduced sensitivity to probabilities and increased sensitivity to outcomes. For some CPT parameters, individual differences were relatively stable across modes of learning. Our results suggest that outcome and probability information translate into systematically different subjective representations in description- versus experience-based choice. At the same time, both types of decisions seem to tap into the same individual-level regularities.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cumulative prospect theory; Decisions from experience; Hierarchical Bayesian modeling; Risky choice

Mesh:

Year:  2016        PMID: 27620961     DOI: 10.1016/j.cognition.2016.08.020

Source DB:  PubMed          Journal:  Cognition        ISSN: 0010-0277


  9 in total

Review 1.  Unpacking buyer-seller differences in valuation from experience: A cognitive modeling approach.

Authors:  Thorsten Pachur; Benjamin Scheibehenne
Journal:  Psychon Bull Rev       Date:  2017-12

2.  Overrepresentation of extreme events in decision making reflects rational use of cognitive resources.

Authors:  Falk Lieder; Thomas L Griffiths; Ming Hsu
Journal:  Psychol Rev       Date:  2017-10-16       Impact factor: 8.934

Review 3.  The relative merit of empirical priors in non-identifiable and sloppy models: Applications to models of learning and decision-making : Empirical priors.

Authors:  Mikhail S Spektor; David Kellen
Journal:  Psychon Bull Rev       Date:  2018-12

4.  Choice adaptation to changing environments: trends, feedback, and observability of change.

Authors:  Erin N McCormick; Samuel J Cheyette; Cleotilde Gonzalez
Journal:  Mem Cognit       Date:  2022-05-23

5.  Context-Dependent Risk Aversion: A Model-Based Approach.

Authors:  Darío Cuevas Rivera; Florian Ott; Dimitrije Markovic; Alexander Strobel; Stefan J Kiebel
Journal:  Front Psychol       Date:  2018-10-26

6.  Within-person adaptivity in frugal judgments from memory.

Authors:  Elisa Filevich; Sebastian S Horn; Simone Kühn
Journal:  Psychol Res       Date:  2017-12-22

7.  Social Influence in Adolescent Decision-Making: A Formal Framework.

Authors:  Simon Ciranka; Wouter van den Bos
Journal:  Front Psychol       Date:  2019-08-29

8.  Probability Distortion Depends on Choice Sequence in Rhesus Monkeys.

Authors:  Simone Ferrari-Toniolo; Philipe M Bujold; Wolfram Schultz
Journal:  J Neurosci       Date:  2019-01-31       Impact factor: 6.167

9.  Experience and rationality under risk: re-examining the impact of sampling experience.

Authors:  Ilke Aydogan; Yu Gao
Journal:  Exp Econ       Date:  2020-01-16
  9 in total

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