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多元定量内容分析×结构方程模型×
领域研究设计研究统计学
方法族Process / pipelineProcess / pipeline
起源年份1969–2000s1921
提出者Rooted in Holsti (1969) and Neuendorf (2002); multivariate extensions developed in communication and political science research from the 1970s onwardSewall Wright
类型Quantitative research designMethod
开创性文献Neuendorf, K. A. (2002). The Content Analysis Guidebook. Sage Publications. ISBN: 978-0761919773Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm. link ↗
别名multivariate QCA, multivariate content analysis, MQCA, multivariate text analysisSEM, path analysis, latent variable modeling, causal modeling
相关63
摘要Multivariate quantitative content analysis (MQCA) is a systematic, replicable approach to measuring multiple attributes of communication content simultaneously and examining how those attributes relate to each other or to external variables. It extends standard content analysis by applying multivariate statistical techniques — such as factor analysis, cluster analysis, regression, or MANOVA — to coded content data, enabling researchers to uncover complex patterns across many variables at once.Structural equation modeling (SEM) is a comprehensive statistical framework combining path analysis (Sewall Wright, 1921) and confirmatory factor analysis to test complex causal models linking observed and latent variables. Formalized by Jöreskog (1973) with LISREL software, SEM enables simultaneous estimation of measurement relationships (how variables measure latent constructs) and structural relationships (how constructs influence outcomes), making it powerful for theory testing in psychology, epidemiology, organizational research, and health sciences where complex mediation, moderation, and latent processes require integrated analysis.
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ScholarGate方法对比: Multivariate Quantitative Content Analysis · Structural Equation Modeling. 于 2026-06-15 检索自 https://scholargate.app/zh/compare