If data exhibit a dimensional structure more complex than what is assumed, key conditional independence assumptions of the hypothesized model do not hold. The current work pursues posterior predictive model checking, a flexible family of Bayesian model checking procedures, as a tool for...

If data exhibit multidimensionality, key conditional independence assumptions of unidimensional models do not hold. The current work pursues posterior predictive model checking (PPMC) as a tool for criticizing models due to unaccounted for dimensions in data structures that follow conjunctive...

Measuring continuous change or growth in individual students' academic abilities over time currently uses several statistical models or transformations to move from data representing a student's correct or incorrect responses on individual test items to inferences about the form and quantity of...