Módszerek összehasonlítása
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| Ordinal Convergent Validity× | Konvergens validitás× | |
|---|---|---|
| Tudományterület | Pszichometria | Pszichometria |
| Módszercsalád | Latent structure | Latent structure |
| Keletkezés éve≠ | 1959 (validity framework); ordinal adaptation 1990s–2000s | 1959 |
| Megalkotó≠ | Polychoric/tetrachoric correlation tradition (Pearson, 1900s); validity framework formalized by Campbell & Fiske (1959) | Donald T. Campbell & Donald W. Fiske |
| Típus≠ | Validity assessment | Validity evidence / construct validation |
| Alapmű≠ | Rhemtulla, M., Brosseau-Liard, P. E., & Savalei, V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychological Methods, 17(3), 354–373. 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≠ | OCV, convergent validity for ordinal scales, polychoric convergent validity, ordinal AVE | convergent construct validity, convergence validity, AVE-based convergent validity |
| Kapcsolódó≠ | 6 | 4 |
| Összefoglaló≠ | Ordinal convergent validity assesses the degree to which indicators of the same latent construct correlate strongly with each other when those indicators are measured on ordinal (e.g., Likert-type) scales. It adapts standard convergent validity procedures — factor loadings, average variance extracted, and HTMT ratios — to account for the discrete, bounded nature of ordinal response categories using polychoric correlations and ordinal-appropriate estimation methods. | 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. |
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