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| Hệ số tin cậy Omega (ω) của McDonald× | Phân tích nhân tố khẳng định (CFA)× | Phân tích nhân tố khám phá (EFA)× | |
|---|---|---|---|
| Lĩnh vực≠ | Trắc lượng tâm lý | Thống kê | Thống kê |
| Họ | Latent structure | Latent structure | Latent structure |
| Năm ra đời≠ | 1999 | 1969 | — |
| Người khởi xướng≠ | Roderick P. McDonald | Karl Jöreskog | — |
| Loại≠ | Reliability coefficient / latent variable model | Confirmatory latent variable model | Latent variable / dimension reduction |
| Công trình gốc≠ | McDonald, R. P. (1999). Test Theory: A Unified Treatment. Lawrence Erlbaum Associates. ISBN: 978-0805830750 | Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363 | Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗ |
| Tên gọi khác≠ | omega reliability, ω coefficient, omega total, omega hierarchical | Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Liên quan≠ | 6 | 4 | 4 |
| Tóm tắt≠ | McDonald's omega is a factor-analysis-based reliability coefficient introduced by Roderick P. McDonald (1999) that quantifies the internal consistency of a composite score without requiring the restrictive assumption that all items contribute equally to the latent factor. It yields two complementary indices: ω_total, which captures overall reliability of the sum score, and ω_hierarchical (ωh), which reports how much of the composite's variance is explained specifically by a single general factor. | Confirmatory factor analysis tests whether a researcher-specified factor structure fits the observed data. Formalised by Karl Jöreskog in 1969, it is the measurement-model step within structural equation modelling and is the standard tool for validating the factorial structure of scales and questionnaires before comparing groups or estimating latent relationships. | Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance. |
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