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Wordscores×Modélisation Exploratoire par Équations Structurelles×
DomainePsychométriePsychométrie
FamilleLatent structureLatent structure
Année d'origine20032009
Auteur d'origineMichael Laver, Kenneth Benoit, John GarryTihomir Asparouhov, Bengt Muthén
TypeText analysis and dimension reductionHybrid exploratory-confirmatory factor modeling
Source fondatriceLaver, 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 ↗
AliasESEM
Apparentées55
RésuméWordscores 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.
ScholarGateJeu de données
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  1. v1
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  3. PUBLISHED

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ScholarGateComparer des méthodes: Wordscores · Exploratory Structural Equation Modeling. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare