方法对比

	多分类测量不变性	多分类验证性因子分析
领域	心理测量学	心理测量学
方法族	Latent structure	Latent structure
起源年份	2000–2004	1984
提出者	Roger E. Millsap, Robert J. Vandenberg	Bengt Muthen
类型	Multi-group confirmatory test	Latent variable / confirmatory measurement model
开创性文献	Millsap, R. E. & Kwok, O.-M. (2004). Evaluating the impact of partial factor loading and intercept invariance on selection utility. Psychological Methods, 9(2), 200–215.	Flora, D. B. & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491.
别名	PMI, ordinal measurement invariance, polytomous factorial invariance, polytomous multi-group measurement invariance	CFA for ordered categories, ordinal CFA, categorical CFA, WLSMV-CFA
相关	5	5
摘要	Polytomous measurement invariance testing evaluates whether a scale with ordered categorical (polytomous) response options — such as Likert-type items — measures the same latent construct in the same way across two or more groups. It extends classical multi-group CFA invariance testing to properly account for the ordinal nature of item responses, ensuring that group comparisons of latent means or factor structures are substantively valid.	Polytomous confirmatory factor analysis (CFA) tests a pre-specified factor structure when items have three or more ordered response categories (e.g., Likert scales). By working with polychoric correlations and robust estimators such as WLSMV, it avoids the distortions that arise when ordered categorical data are treated as continuous.