Robust estimation of area under ROC curve using auxiliary variables in the presence of missing biomarker values.

ABSTRACT: In medical research, the receiver operating characteristic (ROC) curves can be used to evaluate the performance of biomarkers for diagnosing diseases or predicting the risk of developing a disease in the future. The area under the ROC curve (ROC AUC), as a summary measure of ROC curves, is widely utilized, especially when comparing multiple ROC curves. In observational studies, the estimation of the AUC is often complicated by the presence of missing biomarker values, which means that the existing estimators of the AUC are potentially biased. In this article, we develop robust statistical methods for estimating the ROC AUC and the proposed methods use information from auxiliary variables that are potentially predictive of the missingness of the biomarkers or the missing biomarker values. W

SUBMITTER: Long Q 

PROVIDER: S-EPMC8162996 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature