MINERVA-DM: A memory processes model for judgments of likelihood

This article describes an integration of most of the disparate likelihood judgment phenomena in behavioral decision making using a mathematical memory model. A new theory of likelihood judgments based on D. L. Hintzman's (1984, 1988) MINERVA2 memory model is described. The model, MINERVA-DM (DM = decision making), accounts for a wide range of likelihood judgment phenomena including frequency judgments, conditional likelihood judgments, conservatism, the availability and representativeness heuristics, base-rate neglect, the conjunction error, the validity effect, the simulation heuristic, and the hindsight bias. In addition, the authors extend the model to expert probability judgment and show how MINERVA-DM can account for both good and poor calibration (overconfidence) as a function of varying degrees of expertise. The authors' work is presented as a case study of the advantages of applying memory theory to study decision making.