方法对比

	Wordscores	Latent Transition Analysis
领域	心理测量学	心理测量学
方法族	Latent structure	Latent structure
起源年份	2003	2002
提出者	Michael Laver, Kenneth Benoit, John Garry	Linda M. Collins, Stephanie T. Lanza
类型	Text analysis and dimension reduction	Markovian transition between latent states
开创性文献	Laver, M., Benoit, K., & Garry, J. (2003). Extracting policy positions from political texts using words as data. American Political Science Review, 97(2), 311-331.	Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences. Wiley. ISBN: 9780470228395
别名	—	LTA
相关	5	4
摘要	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.	Latent Transition Analysis (LTA) is a method for studying transitions between latent classes over time, developed by Collins and Lanza (2010). LTA combines latent class analysis (grouping individuals into classes) with Markovian transition models to understand how people move between qualitatively distinct states across time periods.