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| Analisi di Ridondanza× | Wordfish× | |
|---|---|---|
| Campo | Psicometria | Psicometria |
| Famiglia | Latent structure | Latent structure |
| Anno di origine≠ | 1977 | 2008 |
| Ideatore≠ | Albert van den Wollenberg | Jonathan Slapin, Svenja-Sophia Proksch |
| Tipo≠ | Asymmetric multivariate analysis | Generative text model for dimension reduction |
| Fonte seminale≠ | van den Wollenberg, A. L. (1977). Redundancy analysis: An alternative for canonical correlation analysis. Psychometrika, 42(2), 207-219. DOI ↗ | 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 ↗ |
| Alias≠ | RDA | — |
| Correlati | 5 | 5 |
| Sintesi≠ | 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. | 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. |
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