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McDonald's hiërarchische omega (ωh)×Confirmatory factor analysis×
VakgebiedPsychometriePsychometrie
FamilieLatent structureLatent structure
Jaar van ontstaan19991969
GrondleggerRoderick P. McDonaldKarl Gustav Jöreskog
TypeReliability / composite score validity coefficientHypothesis-testing latent variable model
Oorspronkelijke bronReise, 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 ↗Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗
Aliassenomega hierarchical, omega-h, bifactor omega, composite score validity coefficientCFA, confirmatory FA, measurement model, restricted factor analysis
Verwant54
SamenvattingMcDonald'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.Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.
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ScholarGateMethoden vergelijken: McDonald's Omega · Confirmatory factor analysis. Geraadpleegd op 2026-06-19 via https://scholargate.app/nl/compare