Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzlīmeņu skalas izstrāde× | Daudzlīmeņu apstiprinošā faktoru analīze (MCFA)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1990s–2000s | 1994 |
| Autors≠ | Raudenbush, Bryk, Hox and colleagues | Bengt O. Muthen |
| Tips≠ | Hierarchical measurement / scale construction | Latent variable model / measurement model |
| Pirmavots≠ | Hox, J. J. (2010). Multilevel Analysis: Techniques and Applications (2nd ed.). Routledge. ISBN: 978-1848728462 | Muthen, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗ |
| Citi nosaukumi | multilevel measurement modeling, hierarchical scale development, MLSEM scale construction, nested data scale development | MCFA, multilevel measurement model, two-level CFA, hierarchical CFA |
| Saistītās≠ | 5 | 6 |
| Kopsavilkums≠ | 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 confirmatory factor analysis tests a pre-specified factor structure while simultaneously accounting for the non-independence of observations caused by clustered data. It decomposes item variance into within-group and between-group components, fitting a separate measurement model at each level, making it the standard tool for validating psychometric scales administered within natural groups such as classrooms, clinics, or organisations. |
| ScholarGateDatu kopa ↗ |
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