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多群体信度分析×多组验证性因子分析 (MG-CFA)×
领域心理测量学心理测量学
方法族Latent structureLatent structure
起源年份1990s–2000s1971
提出者Classical test theory traditions; synthesized in modern practice by Vandenberg & Lance (2000) and Sijtsma (2009)Karl Jöreskog
类型Reliability estimation and comparisonMeasurement model / invariance test
开创性文献Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗
别名reliability comparison across groups, group-specific reliability estimation, multi-sample reliability analysis, cross-group internal consistencyMG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
相关46
摘要Multi-group reliability analysis estimates internal consistency or stability coefficients separately within each group and then formally compares them to determine whether a scale functions with equal precision across populations. It is a foundational step in cross-group measurement research, typically carried out alongside or prior to measurement invariance testing.Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified.
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ScholarGate方法对比: Multi-group Reliability Analysis · Multi-group confirmatory factor analysis. 于 2026-06-17 检索自 https://scholargate.app/zh/compare