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Validation of Probabilistic Predictions

Author

Listed:
  • Michael E. Miller
  • Carl D. Langefeld
  • William M. Tierney
  • Siu L. Hui
  • Clement J. McDonald

Abstract

Current advances in high-speed computing and increased availability of statistical software have led to widespread use of statistical methods for the development of computerized protocols predictive of binary health outcomes. If these predictive algorithms are to be used in settings other than those for which they were developed, e.g., applied in a different geographic setting or extrapolated for use in a slightly different population, then they should be carefully validated to ensure appropriate application. Miller et al. (Stat Med. 1991) provided a comprehensive methodology for external validation of logistic prediction models, and ap plied these methods in a temporal validation setting. In this article, the authors emphasize how these methods can be applied to general forms of probabilistic predictions and provide several SAS® macros for computation of the desired statistics. Key words: validation; logistic regression; predictive probabilities. (Med Decis Making 1993;13:49-58)

Suggested Citation

  • Michael E. Miller & Carl D. Langefeld & William M. Tierney & Siu L. Hui & Clement J. McDonald, 1993. "Validation of Probabilistic Predictions," Medical Decision Making, , vol. 13(1), pages 49-57, February.
    • Handle: RePEc:sae:medema:v:13:y:1993:i:1:p:49-57
    DOI: 10.1177/0272989X9301300107
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    Cited by:

    1. Ja Hyeon Ku & Myong Kim & Seok-Soo Byun & Hyeon Jeong & Cheol Kwak & Hyeon Hoe Kim & Sang Eun Lee, 2015. "External Validation of Models for Prediction of Lymph Node Metastasis in Urothelial Carcinoma of the Bladder," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-10, October.
    2. Kim Wopken & Hendrik P Bijl & Arjen van der Schaaf & Miranda E Christianen & Olga Chouvalova & Sjoukje F Oosting & Bernard F A M van der Laan & Jan L N Roodenburg & C René Leemans & Ben J Slotman & Pa, 2014. "Development and Validation of a Prediction Model for Tube Feeding Dependence after Curative (Chemo-) Radiation in Head and Neck Cancer," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-8, April.
    3. Jan Weymeirsch & Julian Ernst & Ralf Münnich, 2024. "Model Recalibration for Regional Bias Reduction in Dynamic Microsimulations," Mathematics, MDPI, vol. 12(10), pages 1-25, May.
    4. Selin Merdan & Christine L. Barnett & Brian T. Denton & James E. Montie & David C. Miller, 2021. "OR Practice–Data Analytics for Optimal Detection of Metastatic Prostate Cancer," Operations Research, INFORMS, vol. 69(3), pages 774-794, May.

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