เปรียบเทียบวิธี

	โมเดล DINA	Fuzzy-Set Qualitative Comparative Analysis
สาขาวิชา	การวัดทางจิตวิทยา	การวัดทางจิตวิทยา
ตระกูล	Latent structure	Latent structure
ปีกำเนิด	2001	2000
ผู้ริเริ่ม	Brian Junker, Klaas Sijtsma	Charles Ragin
ประเภท	Discrete latent class model	Set-theoretic configurational method
แหล่งต้นตำรับ	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.	Ragin, C. C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago Press.
ชื่อเรียกอื่น	DINA	fsQCA, FSQCA
ที่เกี่ยวข้อง	4	4
สรุป	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.	Fuzzy-Set Qualitative Comparative Analysis (fsQCA) is a set-theoretic method developed by Charles Ragin in the early 2000s that combines the configurational logic of qualitative case studies with the mathematical rigor of fuzzy sets. It bridges qualitative and quantitative research by allowing researchers to examine causal complexity through combinations of conditions (configurations) rather than isolated variables.