A Causal-Model Theory of Conceptual Representation and Categorization

Research output: Contribution to journalArticlepeer-review


This article presents a theory of categorization that accounts for the effects of causal knowledge that relates the features of categories. According to causal-model theory, people explicitly represent the probabilistic causal mechanisms that link category features and classify objects by evaluating whether they were likely to have been generated by those mechanisms. In 3 experiments, participants were taught causal knowledge that related the features of a novel category. Causal-model theory provided a good quantitative account of the effect of this knowledge on the importance of both individual features and interfeature correlations to classification. By enabling precise model fits and interpretable parameter estimates, causal-model theory helps place the theory-based approach to conceptual representation on equal footing with the well-known similarity-based approaches.

Original languageEnglish (US)
Pages (from-to)1141-1159
Number of pages19
JournalJournal of Experimental Psychology: Learning Memory and Cognition
Issue number6
StatePublished - Nov 2003

ASJC Scopus subject areas

  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Linguistics and Language


Dive into the research topics of 'A Causal-Model Theory of Conceptual Representation and Categorization'. Together they form a unique fingerprint.

Cite this