Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Надійна ретестова надійність× | Конфірматорний факторний аналіз (КФА)× | |
|---|---|---|
| Галузь | Психометрія | Психометрія |
| Родина | Latent structure | Latent structure |
| Рік появи≠ | 1990s–2000s | 1969 |
| Автор методу≠ | Built on classical test-retest reliability (Pearson, early 1900s); robust extensions formalized by Wilcox and colleagues from the 1990s onward | Karl Gustav Jöreskog |
| Тип≠ | Reliability / measurement stability | Hypothesis-testing latent variable model |
| Основоположне джерело≠ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Інші назви | robust temporal stability, outlier-resistant retest reliability, robust repeatability coefficient, robust intraclass correlation | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Пов'язані≠ | 3 | 4 |
| Підсумок≠ | Robust test-retest reliability quantifies how consistently a measure ranks or scores the same individuals across two occasions while protecting the estimate from distortion by outliers and non-normal score distributions. It replaces or supplements classical Pearson-based correlation and standard ICC formulas with robust estimators of location, scale, and association. | 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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