Salīdzināt metodes

	Wordscores	Vairākfaktoru analīze
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	2003	1985
Autors	Michael Laver, Kenneth Benoit, John Garry	Brigitte Escofier, Jérôme Pagès
Tips	Text analysis and dimension reduction	Multiblock dimension reduction
Pirmavots	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.	Escofier, B., & Pagès, J. (1985). Analyses factorielles simples et multiples : Objectifs, méthodes et interprétation. Dunod. ISBN: 9782040116835
Citi nosaukumi	—	MFA, MFA multiple
Saistītās	5	5
Kopsavilkums	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.