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多群一般化理論×多群同時確認的因子分析(MG-CFA)×
分野心理測定学心理測定学
系統Latent structureLatent structure
提唱年1963–20011971
提唱者Lee J. Cronbach and colleagues (Cronbach, Gleser, Nanda, Rajaratnam), extended to multi-group contexts by Brennan and othersKarl Jöreskog
種類Variance component / reliability generalizationMeasurement model / invariance test
原典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 ↗
別名MG G-theory, multi-group G-theory, generalizability theory across groups, cross-group G-studyMG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
関連66
概要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 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手法を比較: Multi-group Generalizability Theory · Multi-group confirmatory factor analysis. 2026-06-18に以下より取得 https://scholargate.app/ja/compare