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| Wordscores× | Множественный факторный анализ× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 2003 | 1985 |
| Автор метода≠ | Michael Laver, Kenneth Benoit, John Garry | Brigitte Escofier, Jérôme Pagès |
| Тип≠ | Text analysis and dimension reduction | Multiblock dimension reduction |
| Основополагающий источник≠ | 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 ↗ | Escofier, B., & Pagès, J. (1985). Analyses factorielles simples et multiples : Objectifs, méthodes et interprétation. Dunod. ISBN: 9782040116835 |
| Другие названия≠ | — | MFA, MFA multiple |
| Связанные | 5 | 5 |
| Сводка≠ | 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. | Multiple Factor Analysis (MFA) is a dimension reduction technique developed by Escofier and Pagès (1985) for analyzing multiple groups of variables measured on the same observations. MFA balances the influence of each variable group to provide a unified view of how observations relate across multiple perspectives. |
| ScholarGateНабор данных ↗ |
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