Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Многогрупповая теория элементных ответов (MG-IRT)× | Конфирматорный факторный анализ (КФА)× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1990s | 1969 |
| Автор метода≠ | Multiple contributors; formalized by Birnbaum (1968) for IRT; multi-group extensions developed through 1980s–1990s | Karl Gustav Jöreskog |
| Тип≠ | Latent trait / measurement invariance | Hypothesis-testing latent variable model |
| Основополагающий источник≠ | Embretson, S. E. & Reise, S. P. (2000). Item Response Theory for Psychologists. Lawrence Erlbaum Associates. ISBN: 978-0805828191 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Другие названия | MG-IRT, multiple-group IRT, multi-group latent trait model, IRT across groups | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Связанные≠ | 6 | 4 |
| Сводка≠ | Multi-group item response theory fits IRT models simultaneously across two or more defined groups — such as males and females, or different cultural samples — to determine whether item parameters are invariant across those groups. It is the primary IRT-based framework for testing measurement equivalence and detecting differential item functioning (DIF) at the model level. | 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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