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| Wordscores× | Латентный анализ переходов× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 2003 | 2002 |
| Автор метода≠ | Michael Laver, Kenneth Benoit, John Garry | Linda M. Collins, Stephanie T. Lanza |
| Тип≠ | Text analysis and dimension reduction | Markovian transition between latent states |
| 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 ↗ | Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences. Wiley. ISBN: 9780470228395 |
| Другие названия≠ | — | LTA |
| Связанные≠ | 5 | 4 |
| 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. | Latent Transition Analysis (LTA) is a method for studying transitions between latent classes over time, developed by Collins and Lanza (2010). LTA combines latent class analysis (grouping individuals into classes) with Markovian transition models to understand how people move between qualitatively distinct states across time periods. |
| ScholarGateНабор данных ↗ |
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