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| Bayesiläinen McDonaldin omega× | Vahvistava faktorianalyysi (CFA)× | |
|---|---|---|
| Tieteenala | Psykometriikka | Psykometriikka |
| Menetelmäperhe | Latent structure | Latent structure |
| Syntyvuosi≠ | 1999 (omega); 2010s (Bayesian estimation) | 1969 |
| Kehittäjä≠ | R. P. McDonald (omega); Bayesian extension developed by Kelley, Pornprasertmanit, and others | Karl Gustav Jöreskog |
| Tyyppi≠ | Reliability / internal consistency estimation | Hypothesis-testing latent variable model |
| Alkuperäislähde≠ | Kelley, K. & Pornprasertmanit, S. (2016). Confidence intervals for population reliability coefficients: Evaluation of methods, recommendations, and software for composite measures. Psychological Methods, 21(1), 69–92. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Rinnakkaisnimet | Bayesian omega, Bayesian composite reliability, posterior omega, Bayesian omega total | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Liittyvät≠ | 3 | 4 |
| Tiivistelmä≠ | Bayesian McDonald's omega applies Bayesian statistical estimation to the omega reliability coefficient, yielding a full posterior distribution over omega rather than a single point estimate. This provides credible intervals and probabilistic uncertainty quantification for the reliability of a composite or scale score, making it especially useful for small samples and complex factor structures. | 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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