Hostname: page-component-745bb68f8f-l4dxg Total loading time: 0 Render date: 2025-01-08T16:43:34.987Z Has data issue: false hasContentIssue false

A Lower Bound to the Probability of Choosing the Optimal Passing Score for a Mastery Test when there is an External Criterion

Published online by Cambridge University Press:  01 January 2025

Rand R. Wilcox*
Affiliation:
University of California at Los Angeles
*
Requests for reprints should be sent to Rand R. Wilcox, Center for the Study of Evaluation, UCLA Graduate School of Education, Los Angeles, CA 90024.

Abstract

Recently there has been interest in the problem of determining an optimal passing score for a mastery test when the purpose of the test is to predict success or failure on an external criterion. For the case of constant losses for the two error types, a method of determining an optimal passing score is readily derived using standard techniques. The purpose of this note is to describe a lower bound to the probability of identifying an optimal passing score based on a random sample of N examinees.

Type
Notes And Comments
Copyright
Copyright © 1979 The Psychometric Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

The work upon which this publication is based was performed pursuant to a grant [contract] with the National Institute of Education, Department of Health, Education and Welfare. Points of view or opinions stated do not necessarily represent official NIE position or policy.

References

Reference Note

Novick, M. R. & Lewis, C. Prescribing test length for criterion-referenced measurement. In Harris, C. W., Alkin, M. C. & James Popham, W.(Eds.), Problems in criterion-referenced measurement, 1974, Los Angeles: Center for the Study of Evaluation, University of California.Google Scholar

References

Aitchison, J. & Aitken, C. G. G. Multivariate binary discrimination by the kernel method. Biometrika, 1976, 63, 413420.CrossRefGoogle Scholar
Feller, W. An introduction to probability theory and its applications (Vol. I), 1968, New York: John Wiley.Google Scholar
Gibbons, J., Olkin, I., & Sobel, M. Selecting and ordering populations: A new statistical methodology, 1977, New York: John Wiley.Google Scholar
Griffiths, D. A. Maximum likelihood estimation for the beta-binomial distribution and an application to the household distribution on the total number of cases of a disease. Biometrics, 1973, 29, 637648.CrossRefGoogle Scholar
Huynh, H. Statistical consideration of mastery scores. Psychometrika, 1976, 41, 6578.CrossRefGoogle Scholar
Huynh, H. Two simple classes of mastery scores based on the beta-binomial model. Psychometrika, 1977, 42, 601608.CrossRefGoogle Scholar
Johns, M. V. An empirical Bayes approach to non-parametric two-way classification. In Solomon, H.(Eds.), Studies in Item Analysis and Prediction, 1961, Stanford, CA: Stanford University Press.Google Scholar
Keats, J. A. & Lord, F. M. A theoretical distribution for mental test scores. Psychometrika, 1962, 27, 5972.CrossRefGoogle Scholar
Meredith, W. & Kearns, J. Empirical Bayes point estimates of latent trait scores without knowledge of the trait distribution. Psychometrika, 1973, 38, 533554.CrossRefGoogle Scholar
Lord, F. M. A strong true-score theory, with applications. Psychometrika, 1965, 30, 239270.CrossRefGoogle Scholar
Lord, F. M. & Novick, M. R. Statistical theories of mental test scores, 1968, Reading, Mass.: Addison-Wesley.Google Scholar
Ott, J. & Kronmal, R. A. Some classification procedures for multivariate binary data using orthogonal functions. Journal of the American Statistical Association, 1976, 71, 391399.CrossRefGoogle Scholar
Sobel, M. & Huyett, M. Selecting the best one of several binomial populations. Bell System Technical Journal, 1957, 36, 537576.CrossRefGoogle Scholar
Van der Linden, W. J. & Mellenbergh, G. J. Optimal cutting scores using a linear loss function. Applied Psychological Measurement, 1977, 1, 593599.CrossRefGoogle Scholar
Wilcox, R. R. Estimating the parameters of the beta-binomial distribution. Educational and Psychological Measurement. 1979, in press.CrossRefGoogle Scholar
Zehna, P. W. Invariance of maximum likelihood estimation. Annals of Mathematical Statistics, 1966, 37, 744744.CrossRefGoogle Scholar