In this ITEMS module, we introduce the generalized deterministic inputs, noisy "and" gate (G-DINA) model, which is a general framework for specifying, estimating, and evaluating a wide variety of cognitive diagnosis models. The module contains a nontechnical introduction to diagnostic measurement, an introductory overview of the G-DINA…

Cognitive diagnosis models (CDMs) allow for the extraction of fine-grained, multidimensional diagnostic information from appropriately designed tests. In recent years, interest in such models has grown as formative assessment grows in popularity. Many dichotomous as well as several polytomous CDMs have been proposed in the last two decades, but…

Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study…

As with any psychometric models, the validity of inferences from cognitive diagnosis models (CDMs) determines the extent to which these models can be useful. For inferences from CDMs to be valid, it is crucial that the fit of the model to the data is ascertained. Based on a simulation study, this study investigated the sensitivity of various fit…

The G-DINA ("generalized deterministic inputs, noisy and gate") model is a generalization of the DINA model with more relaxed assumptions. In its saturated form, the G-DINA model is equivalent to other general models for cognitive diagnosis based on alternative link functions. When appropriate constraints are applied, several commonly used…

Cognitive diagnosis models (CDMs), as alternative approaches to unidimensional item response models, have received increasing attention in recent years. CDMs are developed for the purpose of identifying the mastery or nonmastery of multiple fine-grained attributes or skills required for solving problems in a domain. For CDMs to receive wider use,…

Most model fit analyses in cognitive diagnosis assume that a Q matrix is correct after it has been constructed, without verifying its appropriateness. Consequently, any model misfit attributable to the Q matrix cannot be addressed and remedied. To address this concern, this paper proposes an empirically based method of validating a Q matrix used…

In this article, the authors present a multilevel (or hierarchical linear) model that illustrates issues in the application of the model to data from meta-analytic studies. In doing so, several issues are discussed that typically arise in the course of a meta-analysis. These include the presence of non-zero between-study variability, how multiple…