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偏最小二乘结构方程模型×Wordscores×
领域心理测量学心理测量学
方法族Latent structureLatent structure
起源年份19852003
提出者Herman WoldMichael Laver, Kenneth Benoit, John Garry
类型Component-based structural equation modelText analysis and dimension reduction
开创性文献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: 9781483377445Laver, 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 ↗
别名PLS-SEM, PLS path modeling
相关55
摘要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.Wordscores 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.
ScholarGate数据集
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  2. 3 来源
  3. PUBLISHED
  1. v1
  2. 3 来源
  3. PUBLISHED

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ScholarGate方法对比: Partial Least Squares Structural Equation Modeling · Wordscores. 于 2026-06-19 检索自 https://scholargate.app/zh/compare