TY  - JOUR
AU  - Meng, Xing 
AU  - Tubbs, J.D. 
PY  - 2020
TI  - Application of a Beta Regression Model for Covariate Adjusted ROC
JF  - Current Research in Biostatistics
VL  - 10
IS  - 1
DO  - 10.3844/amjbsp.2020.20.24
UR  - https://thescipub.com/abstract/amjbsp.2020.20.24
AB  - The Receiver Operating Characteristic (ROC) curve and the area under the ROC (AUC) are widely used in determining the diagnostic capability of a binary classification procedure. Since the test performance is affected by covariates, the ROC and AUC have been utilized in a Generalized Linear Regression (GLM) setting. In this study, we revisit a problem where the AUC regression model was used in a clinical study with discrete covariates by considering ROC regression models with both discrete and continuous covariates. The two ROC regression models are based upon a widely used parametric model and a recently published model based upon fitting the placement values with the beta distribution. The two methods are illustrated using data from a clinic study.