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…

This paper addresses two Global Matching predictions in embedded-category designs: the within-category choice advantage in forced-choice recognition (superior discrimination for test choices comprising a same-category distractor); and the category length effect in forced-choice and old/new recognition (a loss in discriminability with increases in…

This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that considers an existing model of category representation, the Varying Abstraction Model (VAM), which attempts to infer the representations people use from their behavior in…