Feature-to-feature inference under conditions of Cue restriction and dimensional correlation

Matthew E. Lancaster, Donald Homa

Research output: Contribution to journalArticlepeer-review


The present study explored feature-to- feature and label-to- feature inference in a category task for different category structures. In the correlated condition, each of the 4 dimensions comprising the category was positively correlated to each other and to the category label. In the uncorrelated condition, no correlation existed between the 4 dimensions comprising the category, although the dimension to category label correlation matched that of the correlated condition. After learning, participants made inference judgments of a missing feature, given 1, 2, or 3 feature cues; on half the trials, the category label was also included as a cue. The results showed superior inference of features following training on the correlated structure, with accurate inference when only a single feature was presented. In contrast, a single-feature cue resulted in chance levels of inference for the uncorrelated structure. Feature inference systematically improved with number of cues after training on the correlated structure. Surprisingly, a similar outcome was obtained for the uncorrelated structure, an outcome that must have reflected mediation via the category label. A descriptive model is briefly introduced to explain the results, with a suggestion that this paradigm might be profitably extended to hierarchical structures where the levels of feature-to- feature inference might vary with the depth of the hierarchy.

Original languageEnglish (US)
Pages (from-to)35-45
Number of pages11
JournalAmerican Journal of Psychology
Issue number1
StatePublished - 2017


  • Categorization
  • Concepts
  • Expertise
  • Inductive reasoning
  • Memory

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)


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