Bandingkan metode

	SIBTEST	Pengujian Adaptif Komputerisasi Diagnostik Kognitif	Model DINA	Model DINO
Bidang	Psikometri	Psikometri	Psikometri	Psikometri
Keluarga	Latent structure	Latent structure	Latent structure	Latent structure
Tahun asal	1993	2007	2001	2006
Pencetus	Richard Shealy, William F. Stout	Xueli Xu, Jean-Paul Fox	Brian Junker, Klaas Sijtsma	James Templin, Russell Henson
Tipe	Differential item functioning (DIF) assessment	Skill-adaptive testing with psychometric diagnostic classification	Discrete latent class model	Disjunctive latent class model
Sumber perintis	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.	Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25(3), 258-272.	Templin, J., & Henson, R. A. (2006). Measurement of psychological disorders using cognitive diagnosis models. Psychological Methods, 11(3), 287-305.
Alias	—	CD-CAT	DINA	DINO
Terkait	5	5	4	4
Ringkasan	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.	The DINA Model (Deterministic Inputs, Noisy Outputs) is a cognitive diagnostic model developed by Junker and Sijtsma (2001) that classifies examinees into latent skill classes based on their item response patterns. DINA assumes a deterministic relationship between skill mastery and correct responses, with probabilistic error accounting for guessing and slips.	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.