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أوميغا الهرمية لماكدونالد (ωh)×نموذج العامل الثنائي (العوامل العامة والخاصة)×
المجالالقياس النفسيالقياس النفسي
العائلةLatent structureLatent structure
سنة النشأة19991937
صاحب الطريقةRoderick P. McDonaldHolzinger & Swineford (1937); modern revival by Reise (2012)
النوعReliability / composite score validity coefficientConfirmatory latent variable model
المصدر التأسيسيReise, S. P., Scheines, R., Widaman, K. F. & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling: A bifactor perspective. Educational and Psychological Measurement, 73(1), 5–26. DOI ↗Reise, S. P. (2012). The Rediscovery of Bifactor Measurement Models. Multivariate Behavioral Research, 47(5), 667–696. DOI ↗
الأسماء البديلةomega hierarchical, omega-h, bifactor omega, composite score validity coefficientBifaktör Modeli — Genel ve Spesifik Faktörler, hierarchical factor model, general-specific factor model, Schmid-Leiman model
ذات صلة56
الملخصMcDonald's hierarchical omega (ωh) is a coefficient derived from a bifactor confirmatory factor model that quantifies what proportion of total-score variance is attributable to a single general factor rather than to group-specific factors or item-level error. Introduced by Roderick P. McDonald (1999) and elaborated for bifactor applications by Reise and colleagues (2013) and Rodriguez and colleagues (2016), it is the primary index used in psychometrics to evaluate whether a composite total score is a defensible summary of a multidimensional scale.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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ScholarGateقارن الطرق: McDonald's Omega · Bifactor Model. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare