Cognitive assessment models with few assumptions, and connections with nonparametric item response theory

Some usability and interpretability issues for single-strategy cognitive as sessment models are considered. These models posit a stochastic conjunctive relationship between a set of cognitive attributes to be assessed and perf ormance on particular items/tasks in the assessment. The models considered make few assumptions about the relationship between latent attributes and t ask performance beyond a simple conjunctive structure. An example shows tha t these models. can be sensitive to cognitive attributes, even in data desi gned to well fit the Rasch model. Several stochastic ordering and monotonic ity properties are considered that enhance the interpretability of the mode ls. Simple data summaries are identified that inform about the presence or absence of cognitive attributes when the full computational power needed to estimate the models is not available.