Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тестирование инвариантности порядковых измерений× | Конфирматорный факторный анализ (КФА)× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1984–2011 | 1969 |
| Автор метода≠ | Roger Millsap; Bengt Muthén | Karl Gustav Jöreskog |
| Тип≠ | Multi-group model comparison | Hypothesis-testing latent variable model |
| Основополагающий источник≠ | Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Другие названия | ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Связанные≠ | 6 | 4 |
| Сводка≠ | Ordinal measurement invariance testing evaluates whether a multi-group confirmatory factor model holds equivalent measurement properties across groups when scale items are ordinal — such as Likert-type response scales. It uses polychoric correlations and categorical estimators (WLSMV/DWLS) rather than Pearson-based methods, correcting the systematic bias that arises when ordinal data are treated as continuous. | 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. |
| ScholarGateНабор данных ↗ |
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