统计与决策2024，Vol.40Issue(10)：40-45,6.DOI:10.13546/j.cnki.tjyjc.2024.10.007
典型相关分析与结构方程模型方法的比较研究
A Comparative Study of Canonical Correlation Analysis and Structural Equation Modeling
摘要
Abstract
Canonical Correlation Analysis(CCA)and Structural Equation Modeling(SEM)are more and more widely used,but because of their similarities,researchers often face difficulties in choosing between them.Thus,it is of great significance to distinguish the relationship between the two.Based on the operating environment of SPSS and AMOS,this paper makes a system-atic comparison from the perspectives of functions,fundamental graphics,second order factors,mediating effects and using condi-tions between CCA and SEM.The results go as below:(1)CCA can perform linear combination calculation,directly calculating the relationship between a latent variable and another group of manifest variables,and can effectively deal with the problem of sec-ond-order factor calculation.(2)SEM can show the relationships of multiple latent variables simultaneously,calculate and present error variances and residual,accurately calculate and show mediating effect,use auxiliary criteria to judge the fitness of the model,and modify the model by adjusting the logical relationship between the variables.Its output results are more comprehensive and accurate.(3)CCA is suitable for simple models with two latent variables,while SEM is suitable for complex models with multiple latent variables.Under certain conditions,CCA and SEM can be combined,or CCA can be used instead of SEM.关键词
典型相关分析/结构方程模型/潜变量/负荷量/适配度Key words
canonical correlation analysis/structural equation modeling/latent variable/loading capacity/fit measure分类
数理科学引用本文复制引用
刘怡然,安奉钧..典型相关分析与结构方程模型方法的比较研究[J].统计与决策,2024,40(10):40-45,6.基金项目
四川省智慧警务与国家安全风险治理重点实验室重点项目(ZHZZZD2302) （ZHZZZD2302）
