Title: The Bayesian evaluation of categorization models: Comment on Wills and Pothos (2012)
Authors: Vanpaemel, Wolf ×
Lee, Michael D #
Issue Date: Nov-2012
Publisher: American Psychological Association
Series Title: Psychological Bulletin vol:138 issue:6 pages:1253-1258
Article number: 10.1037/a0028551
Abstract: Wills and Pothos (2012) reviewed approaches to evaluating formal models of categorization, raising a series of worthwhile issues, challenges, and goals. Unfortunately, in discussing these issues and proposing solutions, Wills and Pothos (2012) did not consider Bayesian methods in any detail. This means not only that their review excludes a major body of current work in the field, but also that it does not consider the body of work that provides the best current answers to the issues raised. In this comment, we argue that Bayesian methods can be-and, in most cases, already have been-applied to all the major model evaluation issues raised by Wills and Pothos (2012). In particular, Bayesian methods can address the challenges of avoiding overfitting, considering qualitative properties of data, reducing dependence on free parameters, and testing empirical breadth. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
ISSN: 0033-2909
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Quantitative Psychology and Individual Differences
× corresponding author
# (joint) last author

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