Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzlīmeņu mērījumu ekvitāte× | Testēšana uz mērījumu ekvivalenci× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 2000s | 2000 |
| Autors≠ | Muthén, Asparouhov, and colleagues | Vandenberg & Lance |
| Tips≠ | Measurement model evaluation | Multi-group confirmatory factor analysis procedure |
| Pirmavots≠ | 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 ↗ | Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature. Organizational Research Methods, 3(1), 4–70. DOI ↗ |
| Citi nosaukumi | MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance | Factorial Invariance, Measurement Equivalence, Configural-Metric-Scalar Testing, Ölçüm Değişmezliği |
| Saistītās | 3 | 3 |
| Kopsavilkums≠ | 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. | Measurement invariance testing is a sequence of nested confirmatory factor analysis (CFA) models that examines whether a psychological scale measures the same latent construct in the same way across distinct groups or time points. Systematized and popularized by Vandenberg and Lance (2000), the procedure tests a hierarchy of constraints — from identical factor patterns to identical item intercepts — so that researchers can justify meaningful group comparisons on latent means. |
| ScholarGateDatu kopa ↗ |
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