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| Eksploracyjna analiza czynnikowa (EFA)× | Modelowanie równań strukturalnych (SEM)× | |
|---|---|---|
| Dziedzina | Statystyka | Statystyka |
| Rodzina | Latent structure | Latent structure |
| Rok powstania≠ | — | 1970 |
| Twórca≠ | — | Karl Jöreskog (LISREL framework, 1970s) |
| Typ≠ | Latent variable / dimension reduction | Latent variable / causal modeling |
| Źródło pierwotne≠ | Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗ | Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540 |
| Inne nazwy≠ | common factor analysis, açımlayıcı faktör analizi, factor analysis | Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling |
| Pokrewne≠ | 4 | 5 |
| Podsumowanie≠ | Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance. | Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences. |
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