Simultaneous Comparison of Sensitivities and Specificities of Two Diagnostic Tests Adjusting for Discrete Covariates

Abstract

Adjusting for covariates is important in the study of the performance of diagnostic tests. In this manuscript, the simultaneous comparison of the sensitivities and specificities of two binary diagnostic tests is studied when discrete covariates are observed in all of the individuals in the sample. Four methods are presented to simultaneously compare the two sensitivities and the two specificities: a global hypothesis test and three other methods based on individual comparisons. The maximum likelihood method was applied to adjust the overall estimators of sensitivities and specificities. Simulation experiments were carried out to study the asymptotic behaviors of the four proposed methods when the covariate is binary, giving general rules of application. The results were applied to a real example.