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| Többszintű diszkrimináns validitás× | Multilevel konvergens validitás× | |
|---|---|---|
| Tudományterület | Pszichometria | Pszichometria |
| Módszercsalád | Latent structure | Latent structure |
| Keletkezés éve | 2005 | 2005 |
| Megalkotó≠ | Dyer, Hanges, & Hall; Chen, Sousa, & West | Dyer, Hanges & Hall; Chen, Bliese & Mathieu |
| Típus≠ | Validity evaluation within multilevel CFA | Measurement validity evaluation |
| Alapmű≠ | Dyer, N. G., Hanges, P. J., & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. Leadership Quarterly, 16(1), 149–167. DOI ↗ | Dyer, N. G., Hanges, P. J. & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. Leadership Quarterly, 16(1), 149–167. DOI ↗ |
| Alternatív nevek≠ | multilevel DV, cross-level discriminant validity, hierarchical discriminant validity, ML-DV | cross-level convergent validity, multilevel measurement validity, between-level convergent validity |
| Kapcsolódó≠ | 5 | 4 |
| Összefoglaló≠ | Multilevel discriminant validity evaluates whether theoretically distinct constructs are empirically separable when data are nested within higher-level units such as teams, schools, or organizations. It extends single-level discriminant validity checks into a multilevel confirmatory factor analysis framework, verifying that constructs are distinguishable both within and between levels simultaneously. | Multilevel convergent validity evaluates whether items or scales intended to measure the same construct show coherent, strong associations at each level of a nested data structure — within individuals, within groups, and between groups. It extends classical convergent validity from single-level measurement models into the multilevel confirmatory factor analysis (ML-CFA) framework. |
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