Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Багаторівнева дискримінантна валідність× | Конфірматорний факторний аналіз (КФА)× | |
|---|---|---|
| Галузь | Психометрія | Психометрія |
| Родина | Latent structure | Latent structure |
| Рік появи≠ | 2005 | 1969 |
| Автор методу≠ | Dyer, Hanges, & Hall; Chen, Sousa, & West | Karl Gustav Jöreskog |
| Тип≠ | Validity evaluation within multilevel CFA | Hypothesis-testing latent variable model |
| Основоположне джерело≠ | 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 ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Інші назви | multilevel DV, cross-level discriminant validity, hierarchical discriminant validity, ML-DV | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Пов'язані≠ | 5 | 4 |
| Підсумок≠ | 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. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
| ScholarGateНабір даних ↗ |
|
|