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多层可靠性分析×McDonald's Hierarchical Omega (ωh)×
领域心理测量学心理测量学
方法族Latent structureLatent structure
起源年份20141999
提出者Geldhof, Preacher & ZyphurRoderick P. McDonald
类型Reliability estimation / psychometric modelingReliability / composite score validity coefficient
开创性文献Geldhof, G. J., Preacher, K. J., & Zyphur, M. J. (2014). Reliability estimation in a multilevel confirmatory factor analysis framework. Psychological Methods, 19(1), 72–91. DOI ↗Reise, 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 ↗
别名multilevel omega, within-group reliability, between-group reliability, hierarchical reliabilityomega hierarchical, omega-h, bifactor omega, composite score validity coefficient
相关35
摘要Multilevel reliability analysis estimates the internal consistency of scale scores separately at the within-group (individual) and between-group (cluster) levels. It corrects the bias that arises when ordinary alpha or omega is applied to hierarchically nested data, such as employees within organizations or students within classrooms.McDonald'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.
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ScholarGate方法对比: Multilevel Reliability Analysis · McDonald's Omega. 于 2026-06-18 检索自 https://scholargate.app/zh/compare