Discrete-state models: comment on Pazzaglia, Dube, and Rotello (2013).

Pazzaglia, Dube, and Rotello (2013) have provided a lengthy critique of threshold and continuous models of recognition memory. Although the early pages of their article focus mostly on the problems they see with 3 vintage threshold models compared with models from signal detection theory (SDT), it becomes clear rather quickly that Pazzaglia et al. are concerned more generally with problems they see with multinomial processing tree (MPT) models. First, we focus on Pazzaglia et al.'s discussion of the evidence concerning receiver operating characteristics (ROCs) in simple recognition memory, then we consider problems they raise with a subclass of MPT models for more complex recognition memory paradigms, and finally we discuss the difference between scientific models and measurement models in the context of MPT and SDT models in general. We argue that Pazzaglia et al. have not adequately considered the evidence relevant to the viability of the simple threshold models and that they have not adequately represented the issues concerning validating a cognitive measurement model. We further argue that selective influence studies and model flexibility studies are as important as studies showing that a model can fit behavioral data. In particular, we note that despite over a half century of effort, no generally accepted scientific theory of recognition memory has emerged and that it is unlikely to ever emerge with studies using standard behavioral measures. Instead, we assert that useful measurement models of both the SDT and the MPT type have been and should continue to be developed.