Abstract

In differentiation models, the processes of encoding and retrieval produce an increase in the distribution of memory strength for targets and a decrease in the distribution of memory strength for foils as the amount of encoding increases. This produces an increase in the hit rate and decrease in the false-alarm rate for a strongly encoded compared with a weakly encoded list, consistent with empirical data. Other models assume that the foil distribution is unaffected by encoding manipulations or the foil distribution increases as a function of target strength. They account for the empirical data by adopting a stricter criterion for strongly encoded lists relative to weakly encoded lists. The differentiation and criterion shift explanations have been difficult to discriminate with accuracy measures alone. In this article, reaction time distributions and accuracy measures are collected in a list-strength paradigm and in a response bias paradigm in which the proportion of test items that are targets is manipulated. Diffusion model analyses showed that encoding strength is primarily accounted for by changes in the rate of accumulation of evidence (i.e., drift rate) for both targets and foils and manipulating the proportion of targets is primarily accounted for by changes in response bias (i.e., starting point). The diffusion model analyses is interpreted in terms of predictions of the differentiation models in which subjective memory strength is mapped directly onto drift rate and criterion placement is mapped onto starting point. Criterion shift models require at least 2 types of shifts to account for these findings.

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