Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzlīmeņu skalas izstrāde× | Daudzlīmeņu ticamības analīze× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1990s–2000s | 2014 |
| Autors≠ | Raudenbush, Bryk, Hox and colleagues | Geldhof, Preacher & Zyphur |
| Tips≠ | Hierarchical measurement / scale construction | Reliability estimation / psychometric modeling |
| Pirmavots≠ | Hox, J. J. (2010). Multilevel Analysis: Techniques and Applications (2nd ed.). Routledge. ISBN: 978-1848728462 | Geldhof, G. J., Preacher, K. J., & Zyphur, M. J. (2014). Reliability estimation in a multilevel confirmatory factor analysis framework. Psychological Methods, 19(1), 72–91. DOI ↗ |
| Citi nosaukumi | multilevel measurement modeling, hierarchical scale development, MLSEM scale construction, nested data scale development | multilevel omega, within-group reliability, between-group reliability, hierarchical reliability |
| Saistītās≠ | 5 | 3 |
| 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 reliability analysis estimates the internal consistency of scale scores separately at the within-group (individual) and between-group (cluster) levels. It corrects the bias that arises when ordinary alpha or omega is applied to hierarchically nested data, such as employees within organizations or students within classrooms. |
| ScholarGateDatu kopa ↗ |
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