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	बाइसेशियन आइटम विश्लेषण	विभेदक आइटम कार्यप्रणाली (DIF)
क्षेत्र	मनोमिति	मनोमिति
परिवार	Latent structure	Latent structure
उद्भव वर्ष	1990s–2000s	1970s–1993
प्रवर्तक	Originated in Bayesian psychometrics literature, developed extensively by Jean-Paul Fox and colleagues	William H. Angoff and colleagues (ETS); systematized by Holland & Wainer
प्रकार	Bayesian inference / item-level diagnostics	Item-level bias detection
मौलिक स्रोत	Fox, J.-P. (2010). Bayesian Item Response Modeling: Theory and Applications. Springer.	Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589
उपनाम	BIA, Bayesian classical item analysis, Bayesian item statistics, Bayesian item-level diagnostics	DIF, item bias analysis, measurement non-equivalence, item-level measurement bias
संबंधित	4	5
सारांश	Bayesian item analysis applies Bayesian inference to estimate item-level statistics — difficulty, discrimination, and distractor effectiveness — by combining observed response data with prior knowledge. It produces full posterior distributions over item parameters rather than single point estimates, providing richer uncertainty information especially with small samples.	Differential item functioning identifies test or survey items that behave differently for examinees from different groups — such as gender, ethnicity, or language background — after controlling for the underlying ability or trait being measured. DIF analysis is essential for fairness evaluation in educational testing and psychological scale development.