Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Політомічна інваріантність вимірювання× | Конфірматорний факторний аналіз (КФА)× | |
|---|---|---|
| Галузь | Психометрія | Психометрія |
| Родина | Latent structure | Latent structure |
| Рік появи≠ | 2000–2004 | 1969 |
| Автор методу≠ | Roger E. Millsap, Robert J. Vandenberg | Karl Gustav Jöreskog |
| Тип≠ | Multi-group confirmatory test | Hypothesis-testing latent variable model |
| Основоположне джерело≠ | Millsap, R. E. & Kwok, O.-M. (2004). Evaluating the impact of partial factor loading and intercept invariance on selection utility. Psychological Methods, 9(2), 200–215. link ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Інші назви | PMI, ordinal measurement invariance, polytomous factorial invariance, polytomous multi-group measurement invariance | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Пов'язані≠ | 5 | 4 |
| Підсумок≠ | Polytomous measurement invariance testing evaluates whether a scale with ordered categorical (polytomous) response options — such as Likert-type items — measures the same latent construct in the same way across two or more groups. It extends classical multi-group CFA invariance testing to properly account for the ordinal nature of item responses, ensuring that group comparisons of latent means or factor structures are substantively valid. | 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. |
| ScholarGateНабір даних ↗ |
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