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Zbieżność wskaźników dla danych porządkowych×Analiza rzetelności dla danych porządkowych×
DziedzinaPsychometriaPsychometria
RodzinaLatent structureLatent structure
Rok powstania1959 (validity framework); ordinal adaptation 1990s–2000s2007
TwórcaPolychoric/tetrachoric correlation tradition (Pearson, 1900s); validity framework formalized by Campbell & Fiske (1959)Bruno D. Zumbo and colleagues
TypValidity assessmentInternal consistency reliability estimation
Źródło pierwotneRhemtulla, 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. DOI ↗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. DOI ↗
Inne nazwyOCV, convergent validity for ordinal scales, polychoric convergent validity, ordinal AVEordinal alpha, polychoric reliability, reliability for ordinal scales, ORA
Pokrewne65
PodsumowanieOrdinal 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.
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ScholarGatePorównaj metody: Ordinal Convergent Validity · Ordinal Reliability Analysis. Pobrano 2026-06-18 z https://scholargate.app/pl/compare