方法对比

	序数收敛效度	ordinal reliability analysis
领域	心理测量学	心理测量学
方法族	Latent structure	Latent structure
起源年份	1959 (validity framework); ordinal adaptation 1990s–2000s	2007
提出者	Polychoric/tetrachoric correlation tradition (Pearson, 1900s); validity framework formalized by Campbell & Fiske (1959)	Bruno D. Zumbo and colleagues
类型	Validity assessment	Internal consistency reliability estimation
开创性文献	Rhemtulla, M., Brosseau-Liard, P. E., & Savalei, V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychological Methods, 17(3), 354–373.	Zumbo, B. D., Gadermann, A. M. & Zeisser, C. (2007). Ordinal versions of coefficients alpha and theta as measures of internal consistency for Likert rating scales. Journal of Modern Applied Statistical Methods, 6(1), 21–29.
别名	OCV, convergent validity for ordinal scales, polychoric convergent validity, ordinal AVE	ordinal alpha, polychoric reliability, reliability for ordinal scales, ORA
相关	6	5
摘要	Ordinal convergent validity assesses the degree to which indicators of the same latent construct correlate strongly with each other when those indicators are measured on ordinal (e.g., Likert-type) scales. It adapts standard convergent validity procedures — factor loadings, average variance extracted, and HTMT ratios — to account for the discrete, bounded nature of ordinal response categories using polychoric correlations and ordinal-appropriate estimation methods.	Ordinal reliability analysis estimates the internal consistency of scales whose items are measured on ordered-category (Likert-type) response formats. By basing computations on polychoric correlations rather than Pearson correlations, it corrects for the attenuation that standard Cronbach's alpha produces when responses are discrete and non-normal.