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다집단 문항 반응 함수 (MG-DIF)×다집단 확인적 요인분석 (MG-CFA)×
분야심리측정학심리측정학
계열Latent structureLatent structure
기원 연도1980s-1990s1971
창시자Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF)Karl Jöreskog
유형Measurement bias detectionMeasurement model / invariance test
원전Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936Vandenberg, 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 ↗
별칭MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysisMG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
관련66
요약Multi-group differential item functioning examines whether test or scale items function equivalently across three or more distinct groups — such as gender, ethnicity, or country — after matching respondents on the underlying trait being measured. Items that behave differently across groups threaten fair measurement and valid score comparisons.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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ScholarGate방법 비교: Multi-group Differential Item Functioning · Multi-group confirmatory factor analysis. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare