Examining the Impact of Differential Item Functioning on Classification Accuracy in Cognitive Diagnostic Models.

Cognitive diagnostic models (CDMs) are of growing interest in educational research because of the models' ability to provide diagnostic information regarding examinees' strengths and weaknesses suited to a variety of content areas. An important step to ensure appropriate uses and interpretations from CDMs is to understand the impact of differential item functioning (DIF). While methods of detecting DIF in CDMs have been identified, there is a limited understanding of the extent to which DIF affects classification accuracy.

Examining DIF in the Context of CDMs When the Q-Matrix Is Misspecified.

The rise in popularity and use of cognitive diagnostic models (CDMs) in educational research are partly motivated by the models' ability to provide diagnostic information regarding students' strengths and weaknesses in a variety of content areas. An important step to ensure appropriate interpretations from CDMs is to investigate differential item functioning (DIF). To this end, the current simulation study examined the performance of three methods to detect DIF in CDMs, with particular emphasis on the impact of Q-matrix misspecification on methods' performance.

Factors associated with practicing evidence-based medicine: a study of family medicine residents.

Background: Evidence-based medicine (EBM) plays a critical part in ensuring that practitioners use the soundest available medical procedures while avoiding ineffective ones. As such, it plays a key role in medical residency education. However, little research has shown what factors influence residents' adoption of habits in, self-efficacy in, and skills of EBM.

Membership categorization analysis as an important qualitative method in evaluation.

This paper presents Membership Categorization Analysis (MCA) as a useful qualitative methodology in evaluation study. MCA is closely connected to Conversation Analysis and is most frequently used in Sociology studies. MCA provides evaluators unique insights into the boundaries different categories (e.