方法对比

	稳健模型检验研究	结构方程模型
领域	研究设计	研究统计学
方法族	Process / pipeline	Process / pipeline
起源年份	1988–1998	1921
提出者	Albert Satorra & Peter M. Bentler; Ke-Hai Yuan	Sewall Wright
类型	Quantitative model-testing research design with robust estimation	Method
开创性文献	Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage.	Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm.
别名	robust SEM, robust structural model testing, robust fit evaluation, robust model evaluation research	SEM, path analysis, latent variable modeling, causal modeling
相关	6	3
摘要	Robust model testing research applies structural or path models to data while explicitly accounting for violations of multivariate normality and other distributional assumptions. Rather than discarding non-normal data or forcing transformations, it uses corrected estimators — most notably the Satorra-Bentler scaled chi-square and Yuan-Bentler robust standard errors — to produce trustworthy fit indices and parameter estimates even when classical maximum likelihood assumptions are breached.	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.