Bias effects in a two-stage recognition paradigm: A challenge for ‘pure’ threshold and signal detection models

Abstract

We explored a two-stage recognition memory paradigm in which people first make single-item “studied”/“not studied” decisions and then have a chance to correct their errors in forced-choice trials. Each forced-choice trial included one studied word (“target”) and one non-studied word (“lure”) that received the same previous single-item response. For example, a “studied”-“studied” trial would have a target that was correctly called “studied” and a lure that was incorrectly called “studied.” The two-high-threshold (2HT) model and the unequal-variance signal detection (UVSD) model predict opposite effects of biasing the initial single-item responses on subsequent forced-choice accuracy. Results from two experiments showed that the bias effect is actually near zero and well out of the range of effects predicted by either model. Follow-up analyses showed that the model failures were not a function of experiment artifacts like changing memory states between the two types of recognition trials. Follow-up analyses also showed that the dual process signal detection (DPSD) model made better predictions for the forced-choice data than 2HT and UVSD models.