Bandingkan metode
Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.
| Wordfish× | Pemodelan Persamaan Struktural Eksploratori× | |
|---|---|---|
| Bidang | Psikometri | Psikometri |
| Keluarga | Latent structure | Latent structure |
| Tahun asal≠ | 2008 | 2009 |
| Pencetus≠ | Jonathan Slapin, Svenja-Sophia Proksch | Tihomir Asparouhov, Bengt Muthén |
| Tipe≠ | Generative text model for dimension reduction | Hybrid exploratory-confirmatory factor modeling |
| Sumber perintis≠ | 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 ↗ | Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16(3), 397-438. DOI ↗ |
| Alias≠ | — | ESEM |
| Terkait | 5 | 5 |
| Ringkasan≠ | 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. | Exploratory Structural Equation Modeling (ESEM) is a hybrid approach that combines exploratory factor analysis (EFA) with confirmatory factor analysis (CFA) and path modeling, developed by Asparouhov and Muthén (2009). ESEM relaxes restrictive zero-loading assumptions of traditional CFA, allowing all indicators to load on all factors, which can reveal cross-factor complexity and improve model fit while retaining the ability to test substantive structural theories. |
| ScholarGateSet data ↗ |
|
|