Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzgrupu Makdonalda Omega× | Daudzgrupas apstiprinošā faktoru analīze (MG-CFA)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1999 (multi-group extension: 2000s–2010s) | 1971 |
| Autors≠ | Roderick P. McDonald | Karl Jöreskog |
| Tips≠ | Reliability coefficient (multi-group extension) | Measurement model / invariance test |
| Pirmavots≠ | McDonald, R. P. (1999). Test Theory: A Unified Treatment. Lawrence Erlbaum Associates. ISBN: 978-0805830408 | Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗ |
| Citi nosaukumi | multi-group omega, omega across groups, group-comparative omega, MG-omega | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| Saistītās≠ | 4 | 6 |
| Kopsavilkums≠ | Multi-group McDonald's omega estimates and compares the reliability of a scale across two or more distinct groups. Rooted in confirmatory factor analysis, it uses the factor loadings and unique variances from each group's measurement model to compute omega, then tests whether reliability is statistically equivalent across groups. | Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified. |
| ScholarGateDatu kopa ↗ |
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