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تحلیل عاملی اکتشافی چندسطحی (ML-EFA)×مدل بای‌فکتور (عوامل عمومی و اختصاصی)×
حوزهروان‌سنجیروان‌سنجی
خانوادهLatent structureLatent structure
سال پیدایش19941937
پدیدآورBengt O. MuthénHolzinger & Swineford (1937); modern revival by Reise (2012)
نوعLatent variable / multilevel dimension reductionConfirmatory latent variable model
منبع بنیادینMuthén, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗Reise, S. P. (2012). The Rediscovery of Bifactor Measurement Models. Multivariate Behavioral Research, 47(5), 667–696. DOI ↗
نام‌های دیگرML-EFA, multilevel factor analysis, two-level exploratory factor analysis, hierarchical exploratory factor analysisBifaktör Modeli — Genel ve Spesifik Faktörler, hierarchical factor model, general-specific factor model, Schmid-Leiman model
مرتبط36
خلاصهMultilevel exploratory factor analysis uncovers latent factor structures simultaneously at two or more levels of a data hierarchy — for example, both within individuals and between groups — without imposing a fixed structure in advance. It is essential whenever survey or test items are collected from respondents nested inside classrooms, organisations, or clinics.The bifactor measurement model specifies that every indicator loads simultaneously on a single general factor and on one of several specific (group) factors. Formally introduced by Holzinger and Swineford in 1937 and brought into mainstream psychometrics by Reise (2012), it is now the standard tool for evaluating whether a multidimensional scale can legitimately yield a single composite score.
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ScholarGateمقایسهٔ روش‌ها: Multilevel EFA · Bifactor Model. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare