A semiparametric method for comparing the discriminatory ability of biomarkers subject to limit of detection.

ABSTRACT: Receiver operating characteristic curves and the area under the curves (AUC) are often used to compare the discriminatory ability of potentially correlated biomarkers. Many biomarkers are subject to limit of detection due to the instrumental limitation in measurements and may not be normally distributed. Standard parametric methods assuming normality can lead to biased results when the normality assumption is violated. We propose new estimation and inference procedures for the AUCs of biomarkers subject to limit of detection by using the semiparametric transformation model allowing for heteroscedasticity. We obtain the nonparametric maximum likelihood estimators by maximizing the likelihood for the observed data with limit of detection. The proposed estimators are shown to be consistent, a

SUBMITTER: Yin L 

PROVIDER: S-EPMC6219382 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature