قارن الطرق

	تحليل العوامل الاستكشافي القوي	نظرية الاستجابة للمفردة (IRT)
المجال	القياس النفسي	القياس النفسي
العائلة	Latent structure	Latent structure
سنة النشأة	2000–2003	1952–1968
صاحب الطريقة	Pison, Rousseeuw, Filzmoser, and Croux; Yuan and Bentler (parallel streams)	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
النوع	Latent variable / dimension reduction (robust)	Probabilistic measurement model
المصدر التأسيسي	Yuan, K.-H., & Bentler, P. M. (2000). Robust mean and covariance structure analysis through iteratively reweighted least squares. Psychometrika, 65(1), 43–58.	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
الأسماء البديلة	robust EFA, robust factor analysis, outlier-resistant factor analysis, EFA with robust estimation	IRT, latent trait theory, item characteristic curve theory, modern test theory
ذات صلة	4	5
الملخص	Robust exploratory factor analysis discovers the latent factor structure of a set of items using estimation methods that are resistant to outliers and violations of multivariate normality. It applies the same measurement model as standard EFA but replaces classical covariance estimation with robust counterparts — such as minimum covariance determinant or iteratively reweighted least squares — so that a small fraction of atypical cases cannot distort the recovered factor loadings.	Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons.