Porównaj metody
Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.
| Robust Structural Equation Modeling× | Analiza ścieżek× | |
|---|---|---|
| Dziedzina | Statystyka | Statystyka |
| Rodzina | Latent structure | Latent structure |
| Rok powstania≠ | 1994 | 1921 |
| Twórca≠ | Albert Satorra & Peter M. Bentler | Sewall Wright |
| Typ≠ | Latent variable / path model with robust inference | Causal / mediation model |
| Źródło pierwotne≠ | Satorra, A. & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis (pp. 399–419). Sage. link ↗ | Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20(7), 557–585. link ↗ |
| Inne nazwy | Robust SEM, SEM with robust standard errors, Satorra-Bentler SEM, non-normal SEM | PA, path coefficient analysis, observed-variable SEM, causal path modeling |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | Robust structural equation modeling (Robust SEM) applies the full SEM framework — simultaneous estimation of measurement and structural relations among latent variables — while using corrected test statistics and sandwich standard errors that remain valid when observed data depart from multivariate normality. The Satorra-Bentler scaled chi-square is the most widely used correction. | Path analysis tests a researcher-specified causal diagram among observed variables by decomposing their intercorrelations into direct effects, indirect (mediated) effects, and spurious associations. Developed by Sewall Wright in 1921, it is the observed-variable special case of structural equation modeling and remains a standard tool for theory-driven multivariate causal inference. |
| ScholarGateZbiór danych ↗ |
|
|