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Wordscores×Изследователско моделиране на структурни уравнения×
ОбластПсихометрияПсихометрия
СемействоLatent structureLatent structure
Година на възникване20032009
СъздателMichael Laver, Kenneth Benoit, John GarryTihomir Asparouhov, Bengt Muthén
ТипText analysis and dimension reductionHybrid exploratory-confirmatory factor modeling
Основополагащ източникLaver, M., Benoit, K., & Garry, J. (2003). Extracting policy positions from political texts using words as data. American Political Science Review, 97(2), 311-331. DOI ↗Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16(3), 397-438. DOI ↗
Други названияESEM
Свързани55
РезюмеWordscores 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.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.
ScholarGateНабор от данни
  1. v1
  2. 3 Източници
  3. PUBLISHED
  1. v1
  2. 3 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Wordscores · Exploratory Structural Equation Modeling. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare