Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Метод структурных уравнений на основе частичных наименьших квадратов× | Wordscores× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1985 | 2003 |
| Автор метода≠ | Herman Wold | Michael Laver, Kenneth Benoit, John Garry |
| Тип≠ | Component-based structural equation model | Text analysis and dimension reduction |
| Основополагающий источник≠ | 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 | Laver, M., Benoit, K., & Garry, J. (2003). Extracting policy positions from political texts using words as data. American Political Science Review, 97(2), 311-331. DOI ↗ |
| Другие названия≠ | PLS-SEM, PLS path modeling | — |
| Связанные | 5 | 5 |
| Сводка≠ | 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. | Wordscores is a text-based scaling method developed by Laver, Benoit, and Garry (2003) that estimates the policy positions of political actors based on word frequencies in their texts. By comparing word usage in reference texts of known positions with test texts, the method infers the latent political dimension of any document without requiring manual coding or training data. |
| ScholarGateНабор данных ↗ |
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