EVALUATION OF CONFOUNDING EFFECTS IN ROC STUDIES

In many clinical studies, it is clear that external forces can affect the performance of diagnostic tests, as these factors influence the di stributions of separator variables. A new estimator for the receiver o perating characteristic (ROC) function is proposed; this estimator con verges to the ROC function uniformly on the interval [0, 1]. Using thi s new estimator, the author proposes to use Cox's proportional hazards regression model for the evaluation of confounding effects in ROC stu dies. The method can be used even when concomitant information is only available for the cases, for example, disease severity. A textbook ex ample on prostate cancer is described for illustration.