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| Oméga de McDonald polytomique× | Analyse Factorielle Confirmatoire (AFC)× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 1999 (omega); 2007 (polytomous extension) | 1969 |
| Auteur d'origine≠ | Roderick P. McDonald (omega); extension for polytomous items by Zumbo, Gadermann & Zeisser | Karl Gustav Jöreskog |
| Type≠ | Reliability coefficient | Hypothesis-testing latent variable model |
| Source fondatrice≠ | Zumbo, B. D., Gadermann, A. M., & Zeisser, C. (2007). Ordinal versions of coefficients alpha and theta as measures of internal consistency for Likert rating scales. Journal of Modern Applied Statistical Methods, 6(1), 21–29. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Alias | ordinal omega, omega for polytomous items, categorical omega, omega polychoric | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Apparentées≠ | 3 | 4 |
| Résumé≠ | Polytomous McDonald's omega estimates the internal consistency reliability of a scale composed of ordinal (polytomous) items — such as Likert-type responses — by computing omega from a factor model fitted to the polychoric correlation matrix rather than the Pearson correlation matrix, yielding estimates that are unbiased by the discreteness of item responses. | 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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