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Statistical Inference for False Positive and False Negative Error Rates in Mastery Testing

Published online by Cambridge University Press:  01 January 2025

Huynh Huynh
Huynh Huynh*
Affiliation:
University of South Carolina
*
Requests for reprints should be addressed to Huynh Huynh, College of Education, University of South Carolina, Columbia, South Carolina 29208.
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Abstract

This paper describes an asymptotic inferential procedure for the estimates of the false positive and false negative error rates. Formulas and tables are described for the computations of the standard errors. A simulation study indicates that the asymptotic standard errors may be used even with samples of 25 cases as long as the Kuder-Richardson Formula 21 reliability is reasonably large. Otherwise, a large sample would be required.

Keywords

mastery testingerrors in classificationsdecision errorsdecision accuracybeta-binomial modeltesting for selectionerror rate inference
Type
Original Paper
Information
Psychometrika , Volume 45 , Issue 1 , March 1980 , pp. 107 - 120
Copyright
Copyright © 1980 The Psychometric Society

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Footnotes

This work was performed pursuant to Grant No NIE-G-78-0087 with the National Institute of Education, Department of Health, Education and Welfare, Huynh Huynh, Principal Investigator. Points of view or opinions stated do not necessarily reflect NIE position or policy and no official endorsement should be inferred. The editorial assistance of Joseph C. Saunders is gratefully acknowledged.

References

Reference Notes

Huynh, H. Statistical inference for the kappa and kappamax reliability indices based on the beta-binomial model. Paper presented at the annual meeting of the Psychometric Society meeting. University of North Carolina at Chapel Hill, June 16–17, 1977.Google Scholar
Huynh, H. Statistical inference for false positive and false negative error rates in mastery testing (computer program and tables added). Publication Series in Mastery Testing (Res. Memo. 79–6), University of South Carolina, 1979.Google Scholar

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