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다수준 신뢰도 분석×McDonald's Omega Hierarchical (ωh)×
분야심리측정학심리측정학
계열Latent structureLatent structure
기원 연도20141999
창시자Geldhof, Preacher & ZyphurRoderick P. McDonald
유형Reliability estimation / psychometric modelingReliability / composite score validity coefficient
원전Geldhof, 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 ↗
별칭multilevel omega, within-group reliability, between-group reliability, hierarchical reliabilityomega hierarchical, omega-h, bifactor omega, composite score validity coefficient
관련35
요약Multilevel 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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