Сравнение методов

	Порядковая конвергентная валидность	Надежность для порядковых данных
Область	Психометрия	Психометрия
Семейство	Latent structure	Latent structure
Год появления	1959 (validity framework); ordinal adaptation 1990s–2000s	2007
Автор метода	Polychoric/tetrachoric correlation tradition (Pearson, 1900s); validity framework formalized by Campbell & Fiske (1959)	Bruno D. Zumbo and colleagues
Тип	Validity assessment	Internal consistency reliability estimation
Основополагающий источник	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.
Другие названия	OCV, convergent validity for ordinal scales, polychoric convergent validity, ordinal AVE	ordinal alpha, polychoric reliability, reliability for ordinal scales, ORA
Связанные	6	5
Сводка	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.