Risk-adjusted diagnostic accuracy study
A risk-adjusted diagnostic accuracy study evaluates how well an index test identifies a target condition while explicitly accounting for patient-level risk factors that influence either disease prevalence or test performance. By adjusting for case-mix, it yields accuracy estimates — sensitivity, specificity, and AUC — that are not confounded by the composition of the study sample, enabling fairer comparisons across populations and clinical settings.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Pepe, M. S. (2003). The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford University Press. · ISBN 978-0198509844
- Janes, H., & Pepe, M. S. (2009). Adjusting for covariate effects on classification accuracy using the covariate-adjusted ROC curve. Biometrika, 96(2), 371–382. · DOI 10.1093/biomet/asp002
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