Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Dezvoltarea de scale multinivel× | Invarianța la măsurare multinivel× | |
|---|---|---|
| Domeniu | Psihometrie | Psihometrie |
| Familie | Latent structure | Latent structure |
| Anul apariției≠ | 1990s–2000s | 2000s |
| Autorul original≠ | Raudenbush, Bryk, Hox and colleagues | Muthén, Asparouhov, and colleagues |
| Tip≠ | Hierarchical measurement / scale construction | Measurement model evaluation |
| Sursa seminală≠ | Hox, J. J. (2010). Multilevel Analysis: Techniques and Applications (2nd ed.). Routledge. ISBN: 978-1848728462 | 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 ↗ |
| Denumiri alternative | multilevel measurement modeling, hierarchical scale development, MLSEM scale construction, nested data scale development | MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance |
| Înrudite≠ | 5 | 3 |
| Rezumat≠ | Multilevel scale development constructs and validates measurement instruments for data collected from individuals nested within higher-level units such as classrooms, organizations, or clinics. It partitions item variance into within-group and between-group components, ensuring that reliability and factor structure are evaluated at both levels simultaneously. | 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. |
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