Comparing the Likelihood Ratios of Two Binary Diagnostic Tests in the Presence of Partial Verification

• Published in: Biometrical journal 2005-08, Vol.47 (4), p.442-457
• Main Authors: Roldán Nofuentes, J. A., Luna del Castillo, J. D.
• Format: Article
• Language: English
• Subjects: Algorithms; Alzheimer Disease - diagnosis; Applications; Biology, psychology, social sciences; Computer Simulation; Confidence Intervals; Data Interpretation, Statistical; Diagnosis, Computer-Assisted - methods; Diagnostic test; Exact sciences and technology; Humans; Likelihood Functions; Likelihood ratio; Mathematics; Medical sciences; Models, Biological; Models, Statistical; Nonparametric inference; Parametric inference; Partial verification; Probability and statistics; Reproducibility of Results; Research Design; ROC Curve; Sciences and techniques of general use; Sensitivity and Specificity; Statistics; Verification bias
• ISSN: 0323-3847; 1521-4036
• DOI: 10.1002/bimj.200410134

The comparison of the efficiency of two binary diagnostic tests requires one to know the disease status for all patients in the sample, by applying a gold standard. In two‐phase studies the gold standard is not applied to all patients in a sample, and the problem of partial verification of the disease arises. At present, one of the approaches most used for comparing two binary diagnostic tests are the likelihood ratios. In this study, the maximum likelihood estimators of likelihood ratios are obtained. The tests of hypothesis to compare the likelihood ratios of two binary diagnostic tests when both are applied to the same random sample in the presence of verification bias are deduced, and simulation experiments are performed in order to investigate the asymptotic behaviour of the tests of hypothesis. The results obtained have been applied to the study of Alzheimer's disease. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)