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Session Type: Training Session
Diagnostic classification models (DCMs) are psychometrics tools that focus on providing actionable feedback in the form of examinee attribute classifications. Longitudinal DCMs have been developed and applied as psychometric tools for analyzing diagnostic assessments administered over multiple occasions. Different from traditional psychometric frameworks for growth, which typically provide continuous and norm-referenced growth estimates, longitudinal DCMs provide categorical growth estimates with criterion-referenced interpretations. This workshop focuses on longitudinal DCMs and their application as the psychometric foundation for categorical growth models. After completing this workshop, participants will understand the structure of longitudinal DCMs, be able to estimate longitudinal DCMs using a newly developed R package, and interpret software output.
This session is appropriate for graduate students, researchers, and practitioners at the emerging or experienced level. Participants are expected to have a basic knowledge of DCMs and psychometrics to enroll. This session presents both conceptual and technical content and also provides hands-on experience for participants to apply what they learn. Content will mostly be delivered through lecture, and content will be reinforced using hands-on activities. Instructor will encourage audience participation through questions and allow time for discussions among participants and the instructor.