Accommodating covariates roc analysis
The Statistical Evaluation of Medical Tests for Classification and Prediction.
Adjusting the generalized ROC curve for covariates.
Conclusions: For the adjusted ROC model being applicable, covariate and biomarker distributions must show double binormal distribution. Adjusting for covariate effects on classification accuracy using the covariate-adjusted receiver operating characteristic curve.
Results: According to the simulation study, if biomarker indicators in healthy group are constant and are lower or equal in healthy group than/to disease group, both adjusted AUC (Adj AUC) and AUC have small values and, no significant difference was found between them.
The AUC was significantly larger when the biomarker indicators in disease group were higher.
Ordinal regression methodology for ROC curves derived from correlated data.
A general regression methodology for ROC curve estimation.