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判别分析×验证性因子分析(CFA)×
领域统计学心理测量学
方法族Latent structureLatent structure
起源年份19361969
提出者Ronald A. FisherKarl Gustav Jöreskog
类型Supervised classification and dimension reductionHypothesis-testing latent variable model
开创性文献Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗
别名LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysisCFA, confirmatory FA, measurement model, restricted factor analysis
相关44
摘要Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error.Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.
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ScholarGate方法对比: Discriminant Analysis · Confirmatory factor analysis. 于 2026-06-18 检索自 https://scholargate.app/zh/compare