Purely relative models cannot provide a general account of absolute identification

Abstract

Unidimensional absolute identification-identifying a presented stimulus from an ordered set-is a common component of everyday tasks. Laboratory investigations have mostly used equally spaced stimuli, and the theoretical debate has focused on the merits of purely relative versus purely absolute models. Absolute models incorporate substantial knowledge of the complete set of stimuli, whereas relative models allow only partial knowledge and assume that each stimulus is compared with recently observed stimuli. We test and refute a general prediction made by relative models, that accuracy is very low for some stimulus sequences when the stimuli are unequally spaced. We conclude that, although relative judgment processes may occur in absolute identification, a model must incorporate long-term referents to explain performance with unequally spaced stimuli. This implies that purely relative models cannot provide a general account of absolute identification.