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多群体普遍性理论×多群体测量不变性检验×
领域心理测量学心理测量学
方法族Latent structureLatent structure
起源年份1963–20011971–1993
提出者Lee J. Cronbach and colleagues (Cronbach, Gleser, Nanda, Rajaratnam), extended to multi-group contexts by Brennan and othersJöreskog, K. G. (1971); Meredith, W. (1993)
类型Variance component / reliability generalizationModel comparison / hypothesis testing
开创性文献Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826Vandenberg, 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MG G-theory, multi-group G-theory, generalizability theory across groups, cross-group G-studymeasurement invariance, factorial invariance, cross-group invariance, MI testing
相关66
摘要Multi-group generalizability theory (MG G-theory) extends classical generalizability theory to estimate and compare variance components — attributable to persons, items, raters, occasions, and their interactions — simultaneously across two or more defined groups. It reveals whether a measurement procedure is equally reliable and generalizable for every group studied, supporting fair and equitable score interpretation.Multi-group measurement invariance testing examines whether a latent construct is measured in the same way across two or more distinct groups — such as cultures, genders, or age cohorts. It is a prerequisite for meaningful group comparisons of latent means or relationships, ensuring that observed score differences reflect true differences rather than measurement artifacts.
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ScholarGate方法对比: Multi-group Generalizability Theory · Multi-group measurement invariance. 于 2026-06-19 检索自 https://scholargate.app/zh/compare