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贝叶斯测量不变性检验×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20131971
提出者Bengt Muthen, Tihomir Asparouhov, Rens Van de SchootKarl Jöreskog
类型Bayesian multigroup latent variable testMeasurement model / invariance test
开创性文献Van de Schoot, R., Kluytmans, A., Tummers, L., Lugtig, P., Hox, J., & Muthen, B. (2013). Facing off with Scylla and Charybdis: a comparison of scalar, partial, and the novel possibility of approximate measurement invariance. Frontiers in Psychology, 4, 770. 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Bayesian MI, approximate measurement invariance, Bayesian multigroup CFA invariance, BSEM measurement invarianceMG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
相关66
摘要Bayesian measurement invariance testing evaluates whether a scale's factor loadings and item intercepts are equivalent across groups, using a Bayesian framework that allows parameters to deviate from strict equality by a small, probabilistically specified amount rather than imposing an exact constraint.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: Bayesian Measurement Invariance · Multi-group confirmatory factor analysis. 于 2026-06-18 检索自 https://scholargate.app/zh/compare