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Keywords:

  • diagnostic test;
  • gold standard;
  • Markov chain Monte-Carlo;
  • sensitivity;
  • specificity

Abstract

Receiver operating characteristic (ROC) curves are commonly used to summarize the classification accuracy of diagnostic tests. It is not uncommon in medical practice that multiple diagnostic tests are routinely performed or multiple disease markers are available for the same individuals. When the true disease status is verified by a gold standard (GS) test, a variety of methods have been proposed to combine such potential correlated tests to increase the accuracy of disease diagnosis. In this article, we propose a method of combining multiple diagnostic tests in the absence of a GS. We assume that the test values and their classification accuracies are dependent on covariates. Simulation studies are performed to examine the performance of the combination method. The proposed method is applied to data from a population-based aging study to compare the accuracy of three screening tests for kidney function and to estimate the prevalence of moderate kidney impairment. Copyright © 2011 John Wiley & Sons, Ltd.