A Censored Mixture Model for Modeling Risk Taking

Risk behavior has substantial consequences for health, well-being, and general behavior. The association between real-world risk behavior and risk behavior on experimental tasks is well documented, but their modeling is challenging for several reasons. First, many experimental risk tasks may end pre...

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Bibliographic Details
Published inPsychometrika Vol. 87; no. 3; pp. 1103 - 1129
Main Authors Dijkstra, Nienke F. S., Tiemeier, Henning, Figner, Bernd, Groenen, Patrick J. F.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2022
Springer Nature B.V
Subjects
Application Reviews and Case Studies
Application Reviews and Case Studies (ARCS)
Assessment
Behavioral Science and Psychology
Decision making
Experiments
Gambling
Humanities
Law
Longitudinal studies
Probability
Probability distribution
Psychology
Psychometrics
Statistical Theory and Methods
Statistics for Social Sciences
Testing and Evaluation
censoring
multiple inflated model
Columbia Card Task
Generation R Study
finite mixtures
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Summary:Risk behavior has substantial consequences for health, well-being, and general behavior. The association between real-world risk behavior and risk behavior on experimental tasks is well documented, but their modeling is challenging for several reasons. First, many experimental risk tasks may end prematurely leading to censored observations. Second, certain outcome values can be more attractive than others. Third, a priori unknown groups of participants can react differently to certain risk-levels. Here, we propose the censored mixture model which models risk taking while dealing with censoring, attractiveness to certain outcomes, and unobserved individual risk preferences, next to experimental conditions.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0033-3123
1860-0980
DOI:10.1007/s11336-021-09839-1