Some suggestions for measuring predictive performance (original) (raw)
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An Erratum to this article was published on 01 April 1982
Abstract
The performance of a prediction or measurement method is often evaluated by computing the correlation coefficient and/or the regression of predictions on true (reference) values. These provide, however, only a poor description of predictive performance. The mean squared prediction error (precision) and the mean prediction error (bias) provide better descriptions of predictive performance. These quantities are easily computed, and can be used to compare prediction methods to absolute standards or to one another. The measures, however, are unreliable when the reference method is imprecise. The use of these measures is discussed and illustrated.
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Authors and Affiliations
- Department of Laboratory Medicine, and Department of Medicine, Division of Clinical Pharmacology, University of California, 94143, San Francisco, California
Lewis B. Sheiner & Stuart L. Beal
Authors
- Lewis B. Sheiner
- Stuart L. Beal
Additional information
Work supported in part by Grants GM 26676 and GM 26691
An erratum to this article is available at http://dx.doi.org/10.1007/BF01062337.
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Sheiner, L.B., Beal, S.L. Some suggestions for measuring predictive performance.Journal of Pharmacokinetics and Biopharmaceutics 9, 503–512 (1981). https://doi.org/10.1007/BF01060893
- Received: 13 November 1980
- Revised: 19 January 1981
- Published: 01 August 1981
- Issue date: August 1981
- DOI: https://doi.org/10.1007/BF01060893