Comparar métodos

	Análisis de Fiabilidad Multinivel	Omega jerárquico de McDonald (ωh)
Campo	Psicometría	Psicometría
Familia	Latent structure	Latent structure
Año de origen	2014	1999
Autor original	Geldhof, Preacher & Zyphur	Roderick P. McDonald
Tipo	Reliability estimation / psychometric modeling	Reliability / composite score validity coefficient
Fuente seminal	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.	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.
Alias	multilevel omega, within-group reliability, between-group reliability, hierarchical reliability	omega hierarchical, omega-h, bifactor omega, composite score validity coefficient
Relacionados	3	5
Resumen	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.