Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Теория обобщаемости для порядковых данных× | Порядковый конфирматорный факторный анализ× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1963–2001 | 1984 |
| Автор метода≠ | Lee J. Cronbach and Robert L. Brennan | Bengt O. Muthén |
| Тип≠ | Reliability / generalizability analysis | Latent variable / structural |
| Основополагающий источник≠ | Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826 | Flora, D. B. & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. DOI ↗ |
| Другие названия | Ordinal G-theory, G-theory for ordinal data, ordinal variance component analysis, G-study for ordered categorical data | CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA |
| Связанные | 5 | 5 |
| Сводка≠ | Ordinal generalizability theory extends classical G-theory to the analysis of reliability and measurement error when item responses are ordered categorical (e.g., Likert-type) rather than continuous. It partitions score variance into components attributable to persons, facets, and their interactions, while accounting for the discrete, bounded nature of ordinal rating scales. | Ordinal confirmatory factor analysis (Ordinal CFA) tests a pre-specified factor structure when the observed indicators are ordinal — typically Likert-type survey items. By using polychoric correlations and robust estimators such as WLSMV, it avoids the bias that arises from treating categorical responses as continuous. |
| ScholarGateНабор данных ↗ |
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