Applying confidence accuracy characteristic plots to old/new recognition memory experiments.

Confidence-accuracy characteristic (CAC) plots were developed for use in eyewitness identification experiments, and previous findings show that high confidence indicates high accuracy in all studies of adults with an unbiased lineup. We apply CAC plots to standard recognition memory data by calculating response-based and item-based accuracy, one using false alarms and the other using misses. We use both methods to examine the confidence-accuracy relationship for both correct old responses (hits) and new responses (correct rejections). We reanalysed three sets of published data using these methods and show that the method chosen, as well as the relation of lures to targets, determines the confidence-accuracy relation. Using response-based accuracy for hits, high confidence yields quite high accuracy, and this is generally true with the other methods, especially when lures are unrelated to targets. However, when analyzing correct rejections, the relationship between confidence and accuracy is less pronounced. When lures are semantically related to targets, the various CAC plots show different confidence-accuracy relations. The different methods of calculating CAC plots provide a useful tool in analyzing standard recognition experiments. The results generally accord with unequal-variance signal detection models of recognition memory.