Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Multilevel Measurement Invariance× | Конфірматорний факторний аналіз (КФА)× | |
|---|---|---|
| Галузь | Психометрія | Психометрія |
| Родина | Latent structure | Latent structure |
| Рік появи≠ | 2000s | 1969 |
| Автор методу≠ | Muthén, Asparouhov, and colleagues | Karl Gustav Jöreskog |
| Тип≠ | Measurement model evaluation | Hypothesis-testing latent variable model |
| Основоположне джерело≠ | 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 ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Інші назви | MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Пов'язані≠ | 3 | 4 |
| Підсумок≠ | 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. | 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. |
| ScholarGateНабір даних ↗ |
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