From information processing to decisions : formalizing and comparing probabilistic choice models

Heck, Daniel W. ; Hilbig, Benjamin E. ; Moshagen, Morten

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Document Type: Article
Year of publication: 2017
The title of a journal, publication series: Cognitive psychology
Volume: 96
Page range: 26-40
Place of publication: Amsterdam [u.a.]
Publishing house: Elsevier
ISSN: 0010-0285 , 1095-5623
Publication language: English
Institution: School of Social Sciences > Kognitive Psychologie u. Differentielle Psychologie (Erdfelder)
Subject: 150 Psychology
Abstract: Decision strategies explain how people integrate multiple sources of information to make probabilistic inferences. In the past decade, increasingly sophisticated methods have been developed to determine which strategy explains decision behavior best. We extend these efforts to test psychologically more plausible models (i.e., strategies), including a new, probabilistic version of the take-the-best (TTB) heuristic that implements a rank order of error probabilities based on sequential processing. Within a coherent statistical framework, deterministic and probabilistic versions of TTB and other strategies can directly be compared using model selection by minimum description length or the Bayes factor. In an experiment with inferences from given information, only three of 104 participants were best described by the psychologically plausible, probabilistic version of TTB. Similar as in previous studies, most participants were classified as users of weighted-additive, a strategy that integrates all available information and approximates rational decisions.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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