Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Validitate Convergentă Multi-Grup× | Analiza factoriala confirmativa multi-grup (MG-CFA)× | |
|---|---|---|
| Domeniu | Psihometrie | Psihometrie |
| Familie | Latent structure | Latent structure |
| Anul apariției≠ | 1981 / 2000 | 1971 |
| Autorul original≠ | Fornell & Larcker (convergent validity criteria); Vandenberg & Lance (multi-group extension) | Karl Jöreskog |
| Tip≠ | Validity assessment procedure | Measurement model / invariance test |
| Sursa seminală≠ | Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. DOI ↗ | 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 ↗ |
| Denumiri alternative | cross-group convergent validity, multi-sample convergent validity, MGCFA convergent validity, AVE across groups | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| Înrudite | 6 | 6 |
| Rezumat≠ | Multi-group convergent validity examines whether items purported to measure the same latent construct relate strongly to that construct consistently across distinct subgroups such as demographic categories, cultures, or experimental conditions. It extends single-sample convergent validity checks into a comparative multi-group confirmatory factor analysis framework. | 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. |
| ScholarGateSet de date ↗ |
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