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| Wordfish× | 模糊方差分析 (Fuzzy ANOVA)× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 2008 | 2011 |
| 提出者≠ | Jonathan Slapin, Svenja-Sophia Proksch | Reinhard Viertl |
| 类型≠ | Generative text model for dimension reduction | Analysis of variance for fuzzy data |
| 开创性文献≠ | Slapin, J. B., & Proksch, S. O. (2008). A scaling model for estimating time-series party positions from texts. Journal of Politics, 70(3), 554-569. DOI ↗ | Viertl, R. (2011). Statistical Methods for Fuzzy Data. Wiley. ISBN: 9780470664802 |
| 别名 | — | — |
| 相关≠ | 5 | 4 |
| 摘要≠ | Wordfish is a statistical model for scaling documents on latent dimensions, developed by Slapin and Proksch (2008). Unlike reference-based methods like Wordscores, Wordfish uses a Poisson generative model to jointly estimate word frequencies and document positions without requiring reference texts or manual annotation. It is particularly useful for estimating time-series changes in policy positions and can scale documents from multiple languages simultaneously. | Fuzzy ANOVA extends classical analysis of variance to fuzzy data where observations and group memberships are imprecise or uncertain. Developed by Viertl and others, Fuzzy ANOVA tests whether fuzzy-valued groups differ significantly while accounting for inherent measurement uncertainty. |
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