Process / pipelineClinical / epidemiology
Risk-Adjusted Diagnostic Accuracy Study — Accounting for Patient Case-Mix in Test Evaluation
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.
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Sources
- 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 ↗