Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Invarianța la măsurare multinivel× | Analiza factoriala confirmatorie (CFA)× | |
|---|---|---|
| Domeniu | Psihometrie | Psihometrie |
| Familie | Latent structure | Latent structure |
| Anul apariției≠ | 2000s | 1969 |
| Autorul original≠ | Muthén, Asparouhov, and colleagues | Karl Gustav Jöreskog |
| Tip≠ | Measurement model evaluation | Hypothesis-testing latent variable model |
| Sursa seminală≠ | 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 ↗ |
| Denumiri alternative | MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Înrudite≠ | 3 | 4 |
| Rezumat≠ | 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. |
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