A Censored Mixture Model for Modeling Risk Taking.

Columbia Card Task Generation R Study censoring finite mixtures multiple inflated model

Journal

Psychometrika
ISSN: 1860-0980
Titre abrégé: Psychometrika
Pays: United States
ID NLM: 0376503

Informations de publication

Date de publication:
09 2022
Historique:
received: 10 02 2020
accepted: 30 12 2021
revised: 23 12 2021
pubmed: 11 2 2022
medline: 9 9 2022
entrez: 10 2 2022
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 35143016
doi: 10.1007/s11336-021-09839-1
pii: 10.1007/s11336-021-09839-1
pmc: PMC9433365
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1103-1129

Informations de copyright

© 2022. The Author(s).

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Auteurs

Nienke F S Dijkstra (NFS)

Erasmus University Rotterdam, Rotterdam, The Netherlands.

Henning Tiemeier (H)

Erasmus University Rotterdam, Rotterdam, The Netherlands.
HARVARD T.H. CHAN SCHOOL OF PUBLIC HEALTH, Boston, USA.

Bernd Figner (B)

Radboud University, Behavioural Science Institute and Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.

Patrick J F Groenen (PJF)

Erasmus University Rotterdam, Rotterdam, The Netherlands.

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Classifications MeSH