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تحلیل عاملی اکتشافی مقاوم×تحلیل عاملی تأییدی (CFA)×
حوزهروان‌سنجیروان‌سنجی
خانوادهLatent structureLatent structure
سال پیدایش2000–20031969
پدیدآورPison, Rousseeuw, Filzmoser, and Croux; Yuan and Bentler (parallel streams)Karl Gustav Jöreskog
نوعLatent variable / dimension reduction (robust)Hypothesis-testing latent variable model
منبع بنیادینYuan, K.-H., & Bentler, P. M. (2000). Robust mean and covariance structure analysis through iteratively reweighted least squares. Psychometrika, 65(1), 43–58. DOI ↗Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗
نام‌های دیگرrobust EFA, robust factor analysis, outlier-resistant factor analysis, EFA with robust estimationCFA, confirmatory FA, measurement model, restricted factor analysis
مرتبط44
خلاصهRobust 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.Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.
ScholarGateمجموعه‌داده
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  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Robust Exploratory Factor Analysis · Confirmatory factor analysis. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare