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DINA-Modell×Fuzzy-Set Qualitative Comparative Analysis×
FachgebietPsychometriePsychometrie
FamilieLatent structureLatent structure
Entstehungsjahr20012000
UrheberBrian Junker, Klaas SijtsmaCharles Ragin
TypDiscrete latent class modelSet-theoretic configurational method
Wegweisende QuelleJunker, 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. DOI ↗Ragin, C. C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago Press. DOI ↗
AliasnamenDINAfsQCA, FSQCA
Verwandt44
ZusammenfassungThe 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.
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ScholarGateMethoden vergleichen: DINA Model · Fuzzy-Set Qualitative Comparative Analysis. Abgerufen am 2026-06-20 von https://scholargate.app/de/compare