Jämför metoder

	Kognitiv diagnostisk datoriserad adaptiv testning	DINO-modellen	Necessary Condition Analysis
Ämnesområde	Psykometri	Psykometri	Psykometri
Familj	Latent structure	Latent structure	Latent structure
Ursprungsår	2007	2006	2016
Upphovsperson	Xueli Xu, Jean-Paul Fox	James Templin, Russell Henson	Jan Dul
Typ	Skill-adaptive testing with psychometric diagnostic classification	Disjunctive latent class model	Set-theoretic configurational analysis
Ursprungskälla	Choi, K. M., Lee, Y. S., & Park, Y. S. (2015). What CDM can tell about examinees' strengths and weaknesses: Cognitive diagnostic information in TIMSS. Journal of Educational Evaluation for Policy Analysis, 24(1), 79-100.	Templin, J., & Henson, R. A. (2006). Measurement of psychological disorders using cognitive diagnosis models. Psychological Methods, 11(3), 287-305.	Dul, J. (2016). Necessary Condition Analysis (NCA): Logic and methodology of "necessary but not sufficient" causality. Organizational Research Methods, 19(1), 10-52.
Alias	CD-CAT	DINO	NCA
Närliggande	5	4	5
Sammanfattning	Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT) combines computerized adaptive testing (CAT) with cognitive diagnostic models (CDMs) to efficiently assess students' specific skill profiles. Rather than producing a single overall ability score, CD-CAT adaptively selects items to quickly identify which skills a student has mastered and which need development.	The DINO Model (Deterministic Inputs, Noisy Outputs—Disjunctive) is a cognitive diagnostic model that relaxes DINA's conjunctive (AND) skill requirement logic. DINO assumes an examinee only needs to master one of multiple possible skill pathways to answer an item correctly, making it suitable for scenarios where skills are substitutable or alternative routes to success exist.	Necessary Condition Analysis (NCA) is a set-theoretic method developed by Dul (2016) that identifies conditions necessary (but not necessarily sufficient) for an outcome to occur. Unlike regression, which estimates average effects, NCA identifies absolute thresholds: conditions that must be present at a certain level for the outcome to be possible, regardless of other factors.