Sammenlign metoder

	Wordscores	Partial Least Squares Structural Equation Modeling
Fagområde	Psykometri	Psykometri
Familie	Latent structure	Latent structure
Oprindelsesår	2003	1985
Ophavsperson	Michael Laver, Kenneth Benoit, John Garry	Herman Wold
Type	Text analysis and dimension reduction	Component-based structural equation model
Oprindelig kilde	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.	Hair, 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: 9781483377445
Aliasser	—	PLS-SEM, PLS path modeling
Relaterede	5	5
Resumé	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.	PLS-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.