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| 다집단 판별 타당도 평가× | 다집단 측정 불변성 검정× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1981 (foundational criterion); multi-group extension 1990s–2000s | 1971–1993 |
| 창시자≠ | Fornell & Larcker (for the AVE-based criterion); extended to multi-group settings by the SEM invariance literature | Jöreskog, K. G. (1971); Meredith, W. (1993) |
| 유형≠ | Validity assessment / model comparison | Model comparison / hypothesis testing |
| 원전≠ | 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 ↗ |
| 별칭 | cross-group discriminant validity, multi-sample discriminant validity, MGDV, discriminant validity across groups | measurement invariance, factorial invariance, cross-group invariance, MI testing |
| 관련≠ | 5 | 6 |
| 요약≠ | Multi-group discriminant validity assessment tests whether constructs measured by a scale are empirically distinct not just in one sample but consistently across two or more groups (e.g., cultures, genders, age cohorts). It extends standard discriminant validity criteria — such as the AVE rule and the HTMT ratio — into a multi-group confirmatory factor analysis framework to verify that conceptual distinctness is replicable across subpopulations. | Multi-group measurement invariance testing examines whether a latent construct is measured in the same way across two or more distinct groups — such as cultures, genders, or age cohorts. It is a prerequisite for meaningful group comparisons of latent means or relationships, ensuring that observed score differences reflect true differences rather than measurement artifacts. |
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