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Partial Least Squares Structural Equation Modeling×Wordscores×
ÄmnesområdePsykometriPsykometri
FamiljLatent structureLatent structure
Ursprungsår19852003
UpphovspersonHerman WoldMichael Laver, Kenneth Benoit, John Garry
TypComponent-based structural equation modelText analysis and dimension reduction
UrsprungskällaHair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. ISBN: 9781483377445Laver, 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 ↗
AliasPLS-SEM, PLS path modeling
Närliggande55
SammanfattningPLS-SEM is a variance-based approach to structural equation modeling developed by Herman Wold (1985) that estimates latent variable models by maximizing the variance explained in dependent variables. Unlike covariance-based SEM, PLS-SEM is particularly useful for exploratory research, small to medium samples, complex models with many constructs, and non-normal data.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.
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ScholarGateJämför metoder: Partial Least Squares Structural Equation Modeling · Wordscores. Hämtad 2026-06-19 från https://scholargate.app/sv/compare