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| Multiszintű nomológiai érvényesség× | Konvergens validitás× | |
|---|---|---|
| Tudományterület | Pszichometria | Pszichometria |
| Módszercsalád | Latent structure | Latent structure |
| Keletkezés éve≠ | 2005 | 1959 |
| Megalkotó≠ | Chen, Bliese & Mathieu (building on Cronbach & Meehl) | Donald T. Campbell & Donald W. Fiske |
| Típus≠ | Validity assessment / construct validation | Validity evidence / construct validation |
| Alapmű≠ | Chen, G., Bliese, P. D. & Mathieu, J. E. (2005). Conceptual framework and statistical procedures for delineating and testing multilevel theories of homology. Organizational Research Methods, 8(4), 375–409. DOI ↗ | Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105. DOI ↗ |
| Alternatív nevek≠ | cross-level construct validity, multilevel construct validation, MNV, nomological validity across levels | convergent construct validity, convergence validity, AVE-based convergent validity |
| Kapcsolódó | 4 | 4 |
| Összefoglaló≠ | Multilevel nomological validity evaluates whether a psychological construct and its network of theoretical relationships hold consistently across multiple levels of analysis — such as individual, team, and organization. It extends classical construct validation to nested data structures, ensuring that a measure means the same thing and behaves as theory predicts at each level. | Convergent validity is the degree to which multiple indicators that are theoretically expected to measure the same construct actually correlate with one another. It is one of the two complementary forms of construct validity identified by Campbell and Fiske (1959) and is now routinely assessed via factor loadings and the Average Variance Extracted (AVE) statistic in SEM-based scale validation. |
| ScholarGateAdatkészlet ↗ |
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