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Политомический исследовательский факторный анализ×Теория отклика на задания (IRT)×
ОбластьПсихометрияПсихометрия
СемействоLatent structureLatent structure
Год появления19781952–1968
Автор методаBengt MuthénFrederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
ТипLatent variable / dimension reductionProbabilistic measurement model
Основополагающий источникFlora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. DOI ↗Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗
Другие названияEFA for ordered-categorical data, polychoric EFA, ordinal exploratory factor analysis, polytomous factor analysisIRT, latent trait theory, item characteristic curve theory, modern test theory
Связанные45
СводкаPolytomous exploratory factor analysis extends standard EFA to ordered categorical (Likert-type) response data by replacing the Pearson correlation matrix with a polychoric correlation matrix. It recovers the latent continuous variable that each polytomous item is assumed to reflect, yielding more accurate factor loadings and better-defined factor structures than treating ordinal scores as if they were continuous.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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ScholarGateСравнение методов: Polytomous EFA · Item Response Theory. Получено 2026-06-18 из https://scholargate.app/ru/compare