השוואת שיטות

	ניתוח פריטים בייסיאני	תפקוד פריט דיפרנציאלי (DIF)
תחום	פסיכומטריה	פסיכומטריה
משפחה	Latent structure	Latent structure
שנת המקור	1990s–2000s	1970s–1993
הוגה השיטה	Originated in Bayesian psychometrics literature, developed extensively by Jean-Paul Fox and colleagues	William H. Angoff and colleagues (ETS); systematized by Holland & Wainer
סוג	Bayesian inference / item-level diagnostics	Item-level bias detection
מקור מכונן	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
כינויים	BIA, Bayesian classical item analysis, Bayesian item statistics, Bayesian item-level diagnostics	DIF, item bias analysis, measurement non-equivalence, item-level measurement bias
קשורות	4	5
תקציר	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.