Using hierarchical Bayesian methods to examine the tools of decision-making

Using hierarchical Bayesian methods to examine the tools of decision-making

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Hierarchical Bayesian methods offer a principled and comprehensive way to relate psychological models to data. Here we use them to model the patterns of information search, stopping and deciding in a simulated binary comparison judgment task. The simulation involves 20 subjects making 100 forced cho...

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Bibliographic Details
Main Authors: Michael D. Lee, Benjamin R. Newell, Andreas Glöckner, Benjamin E. Hilbig
Format: Article
Language:English
Published: Cambridge University Press 2011-12-01
Series:Judgment and Decision Making
Subjects:
hierarchical Bayesian models
Bayesian inference
heuristic decision-making
take-the-best
search rules
stopping rules
Online Access:https://www.cambridge.org/core/product/identifier/S1930297500004253/type/journal_article

Internet

https://www.cambridge.org/core/product/identifier/S1930297500004253/type/journal_article

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