Generalizability theory, also called G theory, is a statistical framework, originally introduced by Lee Cronbach, N. Rajaratnam and Goldine Gleser in 1963, for conceptualizing, investigating and designing reliable observations. It is used to determine the reliability, meaning the reproducibility, of measurements taken under specific conditions, and it is particularly useful for assessing the reliability of performance assessments.
Facts
Core ClaimThe reliability of a measurement is decomposed into multiple, separately estimated sources of error called facets (such as person, rater, item and setting), rather than pooled into a single error term as in classical test theory. 1 FAQs
What is a facet in generalizability theory?
A facet is a source of variation that may add error to a measurement.
A facet is a source of variation in a measurement. Facets may include persons, raters, items or forms, time and settings. They are potential sources of error, and the purpose of generalizability theory is to quantify the amount of error caused by each facet and by the interactions of facets.
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Source Wikipedia: Generalizability Theory
Source Wikipedia: Generalizability Theory
Sources
1. Wikipedia: Generalizability Theory
Wikimedia FoundationGeneralizability theory, opening paragraph
Generalizability theory, or G theory, is a statistical framework for conceptualizing, investigating, and designing reliable observations.
Generalizability theory, opening paragraph, third sentence
It was originally introduced by Lee Cronbach, N. Rajaratnam, and Goldine Gleser in 1963.
Developed By: Lee Cronbach, Lead
It was originally introduced by Lee Cronbach, N. Rajaratnam, and Goldine Gleser in 1963.
Developed By: Goldine Gleser, Lead
It was originally introduced by Lee Cronbach, N. Rajaratnam, and Goldine Gleser in 1963.
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