Módszerek összehasonlítása

	SIBTEST	Kognitív diagnosztikai számítógépes adaptív tesztelés	Szükségesfeltétel-analízis
Tudományterület	Pszichometria	Pszichometria	Pszichometria
Módszercsalád	Latent structure	Latent structure	Latent structure
Keletkezés éve	1993	2007	2016
Megalkotó	Richard Shealy, William F. Stout	Xueli Xu, Jean-Paul Fox	Jan Dul
Típus	Differential item functioning (DIF) assessment	Skill-adaptive testing with psychometric diagnostic classification	Set-theoretic configurational analysis
Alapmű	Shealy, R., & Stout, W. F. (1993). A model-based standardization approach that separates true bias/DIF from group differences and detects test bias/DTF. Psychometrika, 58(2), 159-194.	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.	Dul, J. (2016). Necessary Condition Analysis (NCA): Logic and methodology of "necessary but not sufficient" causality. Organizational Research Methods, 19(1), 10-52.
Alternatív nevek	—	CD-CAT	NCA
Kapcsolódó	5	5	5
Összefoglaló	SIBTEST (Simultaneous Item Bias Test) is a non-parametric method for detecting differential item functioning (DIF) and differential test functioning (DTF) developed by Shealy and Stout (1993). Unlike parametric approaches, SIBTEST does not assume a particular item response model and directly tests whether groups differ in their probability of correct responses at equal levels of overall ability.	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.	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.