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चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।

बहुस्तरीय परीक्षण-पुनर्परीक्षण विश्वसनीयता×सामान्यीकरण सिद्धांत (जी-सिद्धांत)×
क्षेत्रमनोमितिमनोमिति
परिवारLatent structureLatent structure
उद्भव वर्ष1979 (ICC foundation); multilevel extension: 1990s–2000s1963–1972
प्रवर्तकShrout & Fleiss (ICC foundation); multilevel extension by Goldstein, Snijders, and othersLee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam
प्रकारReliability estimation under hierarchical dataVariance-components reliability model
मौलिक स्रोतShrout, P. E. & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420–428. DOI ↗Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗
उपनामhierarchical test-retest reliability, multilevel ICC reliability, nested test-retest reliability, ML-TRT reliabilityG-theory, G-study / D-study framework, variance components reliability
संबंधित54
सारांशMultilevel test-retest reliability estimates how consistently a measurement instrument produces the same scores across repeated administrations when observations are nested within higher-level units — such as patients within clinics or students within classrooms. It partitions total score variance across levels using intraclass correlation coefficients derived from multilevel models.Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions.
ScholarGateडेटासेट
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ScholarGateविधियों की तुलना करें: Multilevel Test-Retest Reliability · Generalizability Theory. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare