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Wordfish×Pemodelan Persamaan Struktural Kuasa Dua Separa×
BidangPsikometrikPsikometrik
KeluargaLatent structureLatent structure
Tahun asal20081985
PengasasJonathan Slapin, Svenja-Sophia ProkschHerman Wold
JenisGenerative text model for dimension reductionComponent-based structural equation model
Sumber perintisSlapin, 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 ↗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
AliasPLS-SEM, PLS path modeling
Berkaitan55
RingkasanWordfish 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.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.
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ScholarGateBandingkan kaedah: Wordfish · Partial Least Squares Structural Equation Modeling. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare