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बयेसियन विभेदक वैधता मूल्यांकन (Bayesian Discriminant Validity Assessment)×अभिसारी वैधता×
क्षेत्रमनोमितिमनोमिति
परिवारLatent structureLatent structure
उद्भव वर्ष2020 (Bayesian HTMT formalization); 1959 (discriminant validity concept)1959
प्रवर्तकAdaptation of Campbell & Fiske (1959) discriminant validity into Bayesian CFA framework; Bayesian HTMT formalization by Garnier-Villarreal & Jorgensen (2020)Donald T. Campbell & Donald W. Fiske
प्रकारValidity assessmentValidity evidence / construct validation
मौलिक स्रोतGarnier-Villarreal, M. & Jorgensen, T. D. (2020). Adapting fit indices for Bayesian structural equation modeling: Comparison to maximum likelihood. Psychological Methods, 25(1), 46–70. DOI ↗Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105. DOI ↗
उपनामBayesian HTMT, Bayesian HTMTb, Bayesian discriminant evidence, Bayesian CFA discriminant validityconvergent construct validity, convergence validity, AVE-based convergent validity
संबंधित64
सारांशBayesian discriminant validity assessment evaluates whether two theoretically distinct latent constructs are empirically separable, using posterior distributions and credible intervals rather than single-point null-hypothesis tests. It is applied within Bayesian confirmatory factor analysis or via the Bayesian heterotrait-monotrait ratio (HTMTb) to determine whether constructs measuring different traits are sufficiently differentiated.Convergent validity is the degree to which multiple indicators that are theoretically expected to measure the same construct actually correlate with one another. It is one of the two complementary forms of construct validity identified by Campbell and Fiske (1959) and is now routinely assessed via factor loadings and the Average Variance Extracted (AVE) statistic in SEM-based scale validation.
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ScholarGateविधियों की तुलना करें: Bayesian Discriminant Validity · Convergent Validity. 2026-06-17 को यहाँ से प्राप्त https://scholargate.app/hi/compare