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Bayesovská explorativní faktorová analýza (BEFA)×Teorie odpovědi na položku (IRT)×
OborPsychometrikaPsychometrika
RodinaLatent structureLatent structure
Rok vzniku2004 (Bayesian formulation); factor analysis roots: 19041952–1968
TvůrceLopes & West (seminal Bayesian treatment); roots in classical factor analysis (Spearman, 1904)Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
TypProbabilistic latent variable modelProbabilistic measurement model
Původní zdrojLopes, H. F. & West, M. (2004). Bayesian model assessment in factor analysis. Statistica Sinica, 14(1), 41–67. link ↗Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗
Další názvyBayesian factor analysis, BEFA, Bayesian common factor model, probabilistic factor analysisIRT, latent trait theory, item characteristic curve theory, modern test theory
Příbuzné45
ShrnutíBayesian exploratory factor analysis applies a full probabilistic framework to the common factor model. By placing prior distributions over factor loadings and unique variances, it yields posterior distributions rather than point estimates, quantifies uncertainty around every loading, and can treat the number of factors as an unknown to be inferred from data.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.
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ScholarGatePorovnat metody: Bayesian EFA · Item Response Theory. Získáno 2026-06-17 z https://scholargate.app/cs/compare