Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Багаторівнева змістовна валідність× | Multilevel Measurement Invariance× | |
|---|---|---|
| Галузь | Психометрія | Психометрія |
| Родина | Latent structure | Latent structure |
| Рік появи≠ | 1975–2000s | 2000s |
| Автор методу≠ | Rooted in Lawshe (1975) for content validity; multilevel extension developed through multilevel psychometric literature from the 1990s onward | Muthén, Asparouhov, and colleagues |
| Тип≠ | Validity evaluation / expert judgment | Measurement model evaluation |
| Основоположне джерело≠ | Lynn, M. R. (1986). Determination and quantification of content validity. Nursing Research, 35(6), 382–385. DOI ↗ | Muthén, B. O., & Asparouhov, T. (2009). Multilevel factor analysis of class and student achievement components. Journal of Educational and Behavioral Statistics, 34(2), 250–270. link ↗ |
| Інші назви | hierarchical content validity, nested-data content validity, multilevel scale content evaluation, MCV | MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance |
| Пов'язані≠ | 6 | 3 |
| Підсумок≠ | Multilevel content validity extends the classical content validity framework to settings where items, raters, or respondents are nested within hierarchical structures — such as students within schools, patients within clinics, or items rated by panels from distinct cultural or professional groups. It ensures that scale content is relevant and representative at every level of the hierarchy, not just in the aggregate. | Multilevel measurement invariance testing evaluates whether a latent construct is measured equivalently both within clusters (e.g., individuals within teams) and between clusters (e.g., team-level aggregates). It extends standard measurement invariance procedures to nested data structures commonly encountered in organisational, educational, and cross-cultural research. |
| ScholarGateНабір даних ↗ |
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