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Diagnostics 2011, 1(1), 1-35; doi:10.3390/diagnostics1010001
Review

Bayesian Methods for Medical Test Accuracy

Received: 18 February 2011 / Revised: 12 April 2011 / Accepted: 20 April 2011 / Published: 5 May 2011
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Abstract

Bayesian methods for medical test accuracy are presented, beginning with the basic measures for tests with binary scores: true positive fraction, false positive fraction, positive predictive values, and negative predictive value. The Bayesian approach is taken because of its efficient use of prior information, and the analysis is executed with a Bayesian software package WinBUGS®. The ROC (receiver operating characteristic) curve gives the intrinsic accuracy of medical tests that have ordinal or continuous scores, and the Bayesian approach is illustrated with many examples from cancer and other diseases. Medical tests include X-ray, mammography, ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine and tests based on biomarkers, such as blood glucose values for diabetes. The presentation continues with more specialized methods suitable for measuring the accuracies of clinical studies that have verification bias, and medical tests without a gold standard. Lastly, the review is concluded with Bayesian methods for measuring the accuracy of the combination of two or more tests.
Keywords: Bayesian inference; posterior distribution; prior distribution; ROC curve; verification bias; tests without a gold standard Bayesian inference; posterior distribution; prior distribution; ROC curve; verification bias; tests without a gold standard
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Broemeling, L.D. Bayesian Methods for Medical Test Accuracy. Diagnostics 2011, 1, 1-35.

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