  The Receiver Operating Characteristic (ROC) curve is a useful tool that
measures the discriminating power of a continuous variable or the accuracy of a
pharmaceutical or medical test to distinguish between two conditions or
classes. In certain situations, the practitioner may be able to measure some
covariates related to the diagnostic variable which can increase the
discriminating power of the ROC curve. To protect against the existence of
atypical data among the observations, a procedure to obtain robust estimators
for the ROC curve in presence of covariates is introduced. The considered
proposal focusses on a semiparametric approach which fits a location-scale
regression model to the diagnostic variable and considers empirical estimators
of the regression residuals distributions. Robust parametric estimators are
combined with adaptive weighted empirical distribution estimators to
down-weight the influence of outliers. The uniform consistency of the proposal
is derived under mild assumptions. A Monte Carlo study is carried out to
compare the performance of the robust proposed estimators with the classical
ones both, in clean and contaminated samples. A real data set is also analysed.
