Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Wordfish× | Daļējo mazāko kvadrātu strukturālo vienādojumu modelēšana× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 2008 | 1985 |
| Autors≠ | Jonathan Slapin, Svenja-Sophia Proksch | Herman Wold |
| Tips≠ | Generative text model for dimension reduction | Component-based structural equation model |
| Pirmavots≠ | Slapin, 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 |
| Citi nosaukumi≠ | — | PLS-SEM, PLS path modeling |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. | 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. |
| ScholarGateDatu kopa ↗ |
|
|