Semiparametric Partial Area Under the ROC Curve Estimation Using Test-Dependent Sampling

• Activity Number: 423
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Bethany Horton*+ and Haibo Zhou
• Companies: UNC Chapel Hill and The University of North Carolina at Chapel Hill
• Keywords: Partial area under ROC curve (pAUC) ; Test-dependent sampling ; Biased sampling ; Missing data

Abstract

Partial area under the receiver operating characteristic curve (pAUC) is a summary measure used to describe the ability of a screening test to discriminate between diseased and non-diseased subjects. The pAUC restricts the false positive rate to an interval that is clinically relevant. As evaluating the true disease status can be costly, it is beneficial for researchers to increase study efficiency by allowing selection probabilities to depend on the screening test. We consider a test dependent sampling (TDS) design where TDS inclusion is dependent on a continuous screening test measure. To improve efficiency, this sampling design incorporates a simple random sample and the supplemental TDS component, as opposed to a design using only a simple random sample of the same size. Disease status is known only for those included in the two sampling components. We propose a pAUC estimator which incorporates the TDS, a simple random sample, and the remaining un-sampled portion of the population whose disease status is unknown. Simulations show an increase in efficiency for the proposed estimator compared to other estimators. This translates to a reduction in study cost and subject burden.