An Application of a Bayesian Approach in Diagnostic Testing Problems in the Absence of a Gold Standard

Abstract

A number of methods have been proposed to estimate the parameters of diagnostic tests in the absence of a perfect gold standard. However, these approaches require at least three diagnostic tests to estimate the parameters and most of these methods are inapplicable in point estimation problems involving nonidentifiable parameters. In this article, we describe a method to estimate the properties of various tests for Chlamydia trachomatis. A general approach has been presented to select a range of suitable prior distributions for the diagnostic testing situation required by the Bayesian approach, and the results from this method are compared with those obtained from other methods in context to the Chlamydia example. The effects of different classes of prior distribution such as skeptical, optimistic, and clinical priors on the estimates of the parameters are demonstrated.