Сравнение методов

	Многоуровневый анализ надежности	Иерархическая омега Макдональда (ωh)
Область	Психометрия	Психометрия
Семейство	Latent structure	Latent structure
Год появления	2014	1999
Автор метода	Geldhof, Preacher & Zyphur	Roderick P. McDonald
Тип	Reliability estimation / psychometric modeling	Reliability / composite score validity coefficient
Основополагающий источник	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.
Другие названия	multilevel omega, within-group reliability, between-group reliability, hierarchical reliability	omega hierarchical, omega-h, bifactor omega, composite score validity coefficient
Связанные	3	5
Сводка	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.