Evaluating Diagnostic Tests with Covariate Adjustment

New paper online presenting a unified approach for evaluating diagnostic tests with covariate adjustment using transformation models. This approach allows to estimate receiver operating characteristic (ROC) curves and summary indices while handling the complexities associated with medical data, including non-normal data, covariates that influence the diagnostic potential of a test, ordinal biomarkers, or censored data due to instrument detection limits.

Transformation ROC analysis can be performed using the tram package in R.