On Exemplar-Based Exemplar Representations: Reply to Ennis (1988)

Nosofsky (1986) proposed and tested a unified quantitative approach to modeling performance in tasks of multidimensional stimulus identification and categorization. The approach was based on the assumption that both identification and categorization decisions are governed by similarity comparisons with individually stored exemplars. By modeling patterns of identification confusions, a multidimensional scaling solution for the exemplars was derived. This solution was then used in conjunction with the exemplar-similarity model to predict performance in four separate categorization conditions with the same set of stimuli. A key component assumption was that selective attention processes may systematically modify distances among exemplars in the multidimensional psychological space.