Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Редукционный анализ× | Метод структурных уравнений на основе частичных наименьших квадратов× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1977 | 1985 |
| Автор метода≠ | Albert van den Wollenberg | Herman Wold |
| Тип≠ | Asymmetric multivariate analysis | Component-based structural equation model |
| Основополагающий источник≠ | van den Wollenberg, A. L. (1977). Redundancy analysis: An alternative for canonical correlation analysis. Psychometrika, 42(2), 207-219. DOI ↗ | Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. ISBN: 9781483377445 |
| Другие названия≠ | RDA | PLS-SEM, PLS path modeling |
| Связанные | 5 | 5 |
| Сводка≠ | Redundancy Analysis (RDA) is a multivariate technique developed by van den Wollenberg (1977) that combines multiple regression and principal component analysis. RDA finds linear combinations of predictor variables that best predict variation in response variables, making it ideal for understanding how sets of predictors collectively explain multivariate outcomes. | PLS-SEM is a variance-based approach to structural equation modeling developed by Herman Wold (1985) that estimates latent variable models by maximizing the variance explained in dependent variables. Unlike covariance-based SEM, PLS-SEM is particularly useful for exploratory research, small to medium samples, complex models with many constructs, and non-normal data. |
| ScholarGateНабор данных ↗ |
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