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| 확인적 요인 분석 (CFA)× | McDonald's Omega Hierarchical (ωh)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1969 | 1999 |
| 창시자≠ | Karl Gustav Jöreskog | Roderick P. McDonald |
| 유형≠ | Hypothesis-testing latent variable model | Reliability / composite score validity coefficient |
| 원전≠ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. 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 ↗ |
| 별칭≠ | CFA, confirmatory FA, measurement model, restricted factor analysis | omega hierarchical, omega-h, bifactor omega, composite score validity coefficient |
| 관련≠ | 4 | 5 |
| 요약≠ | 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. | 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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