Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Порядковая номологическая валидность× | Тестирование инвариантности порядковых измерений× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1955 (concept); ordinal application 1990s–present | 1984–2011 |
| Автор метода≠ | Cronbach & Meehl (nomological network concept); ordinal extension in modern psychometrics | Roger Millsap; Bengt Muthén |
| Тип≠ | Validity assessment | Multi-group model comparison |
| Основополагающий источник≠ | Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302. DOI ↗ | Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 |
| Другие названия | nomological validity for ordinal data, ordinal nomological network, construct network validity (ordinal), ordinal criterion-related validity | ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance |
| Связанные≠ | 5 | 6 |
| Сводка≠ | Ordinal nomological validity examines whether a construct measured with ordinal items (e.g., Likert-type scales) behaves in theoretically predicted ways within a nomological network — a web of expected relationships with other constructs and criteria — using methods suited to ordinal data rather than assuming continuous measurement. | 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. |
| ScholarGateНабор данных ↗ |
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