Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Коэффициент надежности Омега Макдональда (ω)× | Конфирматорный факторный анализ (КФА)× | Эксплораторный факторный анализ (ЭФА)× | |
|---|---|---|---|
| Область≠ | Психометрия | Психометрия | Статистика |
| Семейство | Latent structure | Latent structure | Latent structure |
| Год появления≠ | 1999 | 1969 | — |
| Автор метода≠ | Roderick P. McDonald | Karl Gustav Jöreskog | — |
| Тип≠ | Reliability coefficient / latent variable model | Hypothesis-testing latent variable model | Latent variable / dimension reduction |
| Основополагающий источник≠ | McDonald, R. P. (1999). Test Theory: A Unified Treatment. Lawrence Erlbaum Associates. ISBN: 978-0805830750 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ | 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 ↗ |
| Другие названия≠ | omega reliability, ω coefficient, omega total, omega hierarchical | CFA, confirmatory FA, measurement model, restricted factor analysis | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Связанные≠ | 6 | 4 | 4 |
| Сводка≠ | 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 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. | 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. |
| ScholarGateНабор данных ↗ |
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