Compara mètodes

	Anàlisi de Redundància	Wordfish
Camp	Psicometria	Psicometria
Família	Latent structure	Latent structure
Any d'origen	1977	2008
Autor original	Albert van den Wollenberg	Jonathan Slapin, Svenja-Sophia Proksch
Tipus	Asymmetric multivariate analysis	Generative text model for dimension reduction
Font seminal	van den Wollenberg, A. L. (1977). Redundancy analysis: An alternative for canonical correlation analysis. Psychometrika, 42(2), 207-219.	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.
Àlies	RDA	—
Relacionats	5	5
Resum	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.