방법 비교

	베이즈 측정 불변성 검정	다집단 확인적 요인분석 (MG-CFA)
분야	심리측정학	심리측정학
계열	Latent structure	Latent structure
기원 연도	2013	1971
창시자	Bengt Muthen, Tihomir Asparouhov, Rens Van de Schoot	Karl Jöreskog
유형	Bayesian multigroup latent variable test	Measurement model / invariance test
원전	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.	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.
별칭	Bayesian MI, approximate measurement invariance, Bayesian multigroup CFA invariance, BSEM measurement invariance	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
관련	6	6
요약	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.