Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Многогрупповая конвергентная валидность× | Конфирматорный факторный анализ (КФА)× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1981 / 2000 | 1969 |
| Автор метода≠ | Fornell & Larcker (convergent validity criteria); Vandenberg & Lance (multi-group extension) | Karl Gustav Jöreskog |
| Тип≠ | Validity assessment procedure | Hypothesis-testing latent variable model |
| Основополагающий источник≠ | 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 ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Другие названия | cross-group convergent validity, multi-sample convergent validity, MGCFA convergent validity, AVE across groups | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Связанные≠ | 6 | 4 |
| Сводка≠ | 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. | 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. |
| ScholarGateНабор данных ↗ |
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