Abstract

Approaches to model evaluation in terms of Occam's razor or principles of parsimony cannot avoid judgements about the relative importance of aspects of the models. Assumptions about “core processing” are usually considered more important than those related to decision components, but when the decision is related to a central feature of the processing, it becomes extremely difficult to tease apart the influences of core and decision components and to draw sensible conclusions about underlying architecture. It is preferable, where possible, to use experimental procedures that avoid the necessity for subject decisions related to critical aspects of the underlying process.