Summed-similarity models of visual episodic recognition memory successfully predict the variation in false alarm rates across different test items. With data averaged across subjects, Kahana and Sekuler demonstrated that subjects' performance appears to change along with the mean similarity among study items; with high interstimulus similarity, subjects were less likely to commit false alarms to similar lures. We examined this effect in detail by systematically varying the coordinates of study and test items along a critical stimulus dimension and measuring memory performance at each point. To reduce uncontrolled variance associated with individual differences in vision, the coordinates of study and test items were scaled according to each subject's discrimination threshold. Fitting each of four summed-similarity models to the individual subjects' data demonstrated a clear superiority for models that take account of interitem similarity on a trialwise basis.