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Parciální metoda nejmenších čtverců v modelování pomocí strukturálních rovnic×Wordfish×
OborPsychometrikaPsychometrika
RodinaLatent structureLatent structure
Rok vzniku19852008
TvůrceHerman WoldJonathan Slapin, Svenja-Sophia Proksch
TypComponent-based structural equation modelGenerative text model for dimension reduction
Původní zdrojHair, 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: 9781483377445Slapin, 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 ↗
Další názvyPLS-SEM, PLS path modeling
Příbuzné55
ShrnutíPLS-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.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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ScholarGatePorovnat metody: Partial Least Squares Structural Equation Modeling · Wordfish. Získáno 2026-06-17 z https://scholargate.app/cs/compare