A similarity-based range-frequency model for two-category rating data.

This research examines whether an extension of range-frequency theory (Parducci, 1965) could successfully predict context effects on discrimination between stimuli for two-category rating data. The new model proposes that similarity comparisons between stimulus values and rating category prototypes take place on an implicit range-frequency scale, and thus it entails effects of context on both mean ratings and discrimination indices. Predictions of the similarity-based range-frequency model were tested in an experiment in which the frequency distribution was manipulated by varying the range and relative frequencies of squares, with participants rating square sizes on a two-category scale. The model provided a parsimonious account of how discriminability of common stimuli increases with a decrease in stimulus range or an increase in the density of stimuli within a subrange.