ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

结构方程模型 (SEM)×路径分析×
领域统计学统计学
方法族Latent structureLatent structure
起源年份19701921
提出者Karl Jöreskog (LISREL framework, 1970s)Sewall Wright
类型Latent variable / causal modelingCausal / mediation model
开创性文献Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20(7), 557–585. link ↗
别名Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modelingPA, path coefficient analysis, observed-variable SEM, causal path modeling
相关55
摘要Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences.Path analysis tests a researcher-specified causal diagram among observed variables by decomposing their intercorrelations into direct effects, indirect (mediated) effects, and spurious associations. Developed by Sewall Wright in 1921, it is the observed-variable special case of structural equation modeling and remains a standard tool for theory-driven multivariate causal inference.
ScholarGate数据集
  1. v1
  2. 3 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: SEM · Path Analysis. 于 2026-06-15 检索自 https://scholargate.app/zh/compare