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Published on: February 5, 2014
Generalizability theory for the perplexed: a practical introduction and guide: AMEE Guide No. 68
1Faculty of Health Sciences, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada. blochr@mcmaster.ca
Background:
Generalizability theory (G theory) is a statistical method to analyze the results of psychometric tests, such as tests of performance like the Objective Structured Clinical Examination, written or computer-based knowledge tests, rating scales, or self-assessment and personality tests. It is a generalization of classical reliability theory, which examines the relative contribution of the primary variable of interest, the performance of subjects, compared to error variance. In G theory, various sources of error contributing to the inaccuracy of measurement are explored. G theory is a valuable tool in judging the methodological quality of an assessment method and improving its precision.
Aim:
Starting from basic statistical principles, we gradually develop and explain the method. We introduce tools to perform generalizability analysis, and illustrate the use of generalizability analysis with a series of common, practical examples in educational practice.
Conclusion:
We realize that statistics and mathematics can be either boring or fearsome to many physicians and educators, yet we believe that some foundations are necessary for a better understanding of generalizability analysis. Consequently, we have tried, wherever possible, to keep the use of equations to a minimum and to use a conversational and slightly "off-serious" style.
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