Journal of Agricultural, Biological, and Environmental Statistics

, 11:210

Bayesian inferences for receiver operating characteristic curves in the absence of a gold standard

  • Young-Ku Choi
  • Wesley O. Johnson
  • Michael T. Collins
  • Ian A. Gardner

DOI: 10.1198/108571106X110883

Cite this article as:
Choi, YK., Johnson, W.O., Collins, M.T. et al. JABES (2006) 11: 210. doi:10.1198/108571106X110883


Sensitivity and specificity are used to characterize the accuracy of a diagnostic test. Receiver operating characteristic (ROC) analysis can be used more generally to plot the sensitivity versus (1-specificity) over all possible cutoff points. We develop an ROC analysis that can be applied to diagnostic tests with and without a gold standard. Moreover, the method can be applied to multiple correlated diagnostic tests that are used on the same individual. Simulation studies were performed to assess the discrimination ability of the no-gold-standard method compared with the situation where a gold standard exists. We used the area under the ROC curve (AUC) to quantify the diagnostic accuracy of tests and the difference between AUCs to compare their accuracies. In particular, we can estimate the prevalence of disease/infection under the no-gold-standard method. The method we proposed works well in the absence of a gold standard for correlated test data. Correlation affected the width of posterior probability intervals for these differences. The proposed method was used to analyze ELISA test scores for Johne’s disease in dairy cattle.

Key Words

Diagnostic testMarkov chain Monte CarloSensitivitySerologySpecificity

Copyright information

© International Biometric Society 2006

Authors and Affiliations

  • Young-Ku Choi
    • 1
  • Wesley O. Johnson
    • 2
  • Michael T. Collins
    • 3
  • Ian A. Gardner
    • 4
  1. 1.Methodology Research Core, Institute for Health Research and PolicyUniversity of Illinois at ChicagoChicago
  2. 2.Department of StatisticsUniversity of CaliforniaIrvine
  3. 3.Department of Pathobiological Sciences, School of Veterinary MedicineUniversity of WisconsinMadison
  4. 4.Department of Medicine and Epidemiology, School of Veterinary MedicineUniversity of CaliforniaDavis