Порівняння методів

	Теорія генералізованості (G-Theory)	Конфірматорний факторний аналіз	Надійність між експертами (каппа Коена та ICC)
Галузь	Психометрія	Психометрія	Психометрія
Родина	Latent structure	Latent structure	Latent structure
Рік появи	1963	1969	1960 (kappa); 1979 (ICC)
Автор методу	Lee J. Cronbach and colleagues	Karl Jöreskog	Cohen (kappa, 1960); Shrout & Fleiss (ICC, 1979)
Тип	ANOVA-based variance-component framework	Measurement model / latent variable analysis	Reliability / agreement analysis
Основоположне джерело	Brennan, R. L. (2001). Generalizability Theory. Springer.	Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). Guilford Press. ISBN: 978-1462515363	Cohen, J. (1960). A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 20(1), 37–46.
Інші назви	Generalizability Theory, G-Study / D-Study framework, Genellenebilirlik Kuramı (G-Kuramı)	Doğrulayıcı Faktör Analizi — Ölçek Doğrulama (CFA), confirmatory factor analysis, measurement model testing	inter-rater reliability, interrater agreement, rater agreement, Değerlendiriciler Arası Güvenilirlik (Cohen's κ, ICC)
Пов'язані	6	6	6
Підсумок	Generalizability Theory, developed by Lee J. Cronbach and colleagues in the 1960s and formalised by Brennan (2001), is an ANOVA-based framework that extends Classical Test Theory by decomposing observed score variance into multiple, separately identified sources of measurement error — such as raters, tasks, occasions, or items — rather than bundling all error into a single undifferentiated term.	Confirmatory factor analysis is a measurement modelling technique that tests whether a hypothesised factor structure — typically derived from theory or an earlier exploratory analysis — fits observed data from a new sample. Developed by Karl Jöreskog in 1969, it became the dominant tool for validating psychological scales because it requires the researcher to specify in advance which items belong to which latent factor and then assesses the adequacy of that specification against explicit statistical fit criteria.	Interrater reliability quantifies the degree to which two or more independent raters produce consistent scores when evaluating the same individuals or products. The family encompasses Cohen's kappa, introduced in 1960 for categorical judgments, and the Intraclass Correlation Coefficient (ICC) for continuous ratings, together spanning most measurement scenarios encountered in behavioral, health, and educational research.