পদ্ধতির তুলনা করুন

	Generalizability Theory (G-Theory)	দ্বি-প্যারামিটার লজিস্টিক আইআরটি মডেল (2PL)	নিশ্চায়ক গাঠনিক বিশ্লেষণ
ক্ষেত্র	মনোমিতি	মনোমিতি	মনোমিতি
পরিবার	Latent structure	Latent structure	Latent structure
উদ্ভবের বছর	1963	1980	1969
প্রবর্তক	Lee J. Cronbach and colleagues	Frederic M. Lord	Karl Jöreskog
ধরন	ANOVA-based variance-component framework	Item response model / latent trait model	Measurement model / latent variable analysis
মৌলিক উৎস	Brennan, R. L. (2001). Generalizability Theory. Springer.	Lord, F. M. (1980). Applications of Item Response Theory to Practical Testing Problems. Erlbaum.	Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). Guilford Press. ISBN: 978-1462515363
অপর নাম	Generalizability Theory, G-Study / D-Study framework, Genellenebilirlik Kuramı (G-Kuramı)	two-parameter logistic model, 2PL model, 2PL IRT — İki Parametreli Madde Tepki Modeli	Doğrulayıcı Faktör Analizi — Ölçek Doğrulama (CFA), confirmatory factor analysis, measurement model testing
সম্পর্কিত	6	6	6
সারসংক্ষেপ	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.	The two-parameter logistic item response model, formalised by Frederic Lord (1980), describes the probability that a respondent answers a binary test item correctly as a smooth S-shaped function of the respondent's latent ability. By estimating a separate discrimination parameter for each item alongside a difficulty parameter, 2PL allows items to differ in how sharply they distinguish high- from low-ability respondents — making it the standard model for large-scale educational and psychological assessments.	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.