Heuristic and linear models of judgment: Matching rules and environments.

Détails

ID Serval
serval:BIB_C3BE6D98AF82
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Heuristic and linear models of judgment: Matching rules and environments.
Périodique
Psychological Review, 114(3), 733-758.
Auteur⸱e⸱s
Hogarth R. M., Karelaia N.
Statut éditorial
Publié
Date de publication
2007
Résumé
Much research has highlighted incoherent implications of judgmental heuristics, yet other findings have demonstrated high correspondence between predictions and outcomes. At the same time, judgment has been well modeled in the form of as if linear models. Accepting the probabilistic nature of the environment, the authors use statistical tools to model how the performance of heuristic rules varies as a function of environmental characteristics. They further characterize the human use of linear models by exploring effects of different levels of cognitive ability. They illustrate with both theoretical analyses and simulations. Results are linked to the empirical literature by a meta-analysis of lens model studies. Using the same tasks, the authors estimate the performance of both heuristics and humans where the latter are assumed to use linear models. Their results emphasize that judgmental accuracy depends on matching characteristics of rules and environments and highlight the trade-off between using linear models and heuristics. Whereas the former can be cognitively demanding, the latter are simple to implement. However, heuristics require knowledge to indicate when they should be used.
Création de la notice
19/11/2007 10:47
Dernière modification de la notice
20/08/2019 15:39
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