Traps in the route to models of memory and decision

It is proposed that the products of investigations of learning, memory, and decision over the last half century that are most likely to endure have resulted from interactions between models and experimental research. In this article, some of the traps that must be coped with to make fruitful interactions possible are examined and illustrated with case studies from research on probability learning, category learning, and recognition memory. Topics addressed include functions of models in research; the logic of model testing; fitting models to signal plus noise; values and hazards of averaging data; and potential contributions of neural science to the development of cognitive models.