Description

Measuring the accuracy of diagnostic tests is crucial in many application areas in particular medicine and health care. Good methods for determining diagnostic accuracy provide useful guidance on selection of patient treatment according to the severity of their health status. The receiver operating characteristic (ROC) curve, for example, has proven to be a useful tool to assess the ability of a diagnostic test to discriminate among different groups.

There are many interesting topics you can choose from, to name a few;

• Combination and pooling of Biomarkers
• Bayesian ROC methods
• Multireader ROC analysis
• ROC analysis to compare machine learning models for biomedicine
• ROC Analysis for classification and prediction
• Free-response ROC analysis
• Convex hull ROC curves
• Meta-analysis and ROC curves
• ROC hyper-surface

Prerequisites

• Statistical Inference
• Statistical Modelling or Data Science and Statistical Computing
• Familiarity with the statistical software R (recommended)

References

Articles (pdfs)

• Fawcett, T. An introduction to ROC analysis. Pattern Recognition Letters, 27, 8, 861–874, 2006. [PDF]
• Kamarudin, A.N., Cox, T. & Kolamunnage-Dona, R. Time-dependent ROC curve analysis in medical research: current methods and applications. BMC Med Res Methodol 17, 53, 2017. [PDF]
• Hsu, M., Chang, Y.I. & Hsueh, H. Biomarker selection for medical diagnosis using the partial area under the ROC curve. BMC Res Notes 7, 25, 2014. [PDF]
• Mandrekar, J.N. Receiver Operating Characteristic Curve in Diagnostic Test Assessment. Journal of Thoracic Oncology, 5, 9, 1315-1316, 2010. [PDF]
• Park, S.H., Goo, J.M. & Jo, C.H. Receiver operating characteristic (ROC) curve: practical review for radiologists. Korean journal of radiology, 51, 11–18, 2004. [PDF]
• Goncalves, L., Subtil, A., Oliveira, M. & Bermudez, P. ROC curve estimation: an overview. REVSTAT Statistical Journal, 12, 1-20, 2014. [PDF]
• Pardo-Fernandez, J.C., Rodriguez-Alvarez, M.X. & VanKeilegom, I. A review on ROC curves in the presence of covariates. REVSTAT Statistical Journal, 12, 21–41, 2014. [PDF]
• Nakas, C. T. Developments in roc surface analysis and assessment of diagnostic markers in three-class classification problems. REVSTAT Statistical Journal, 12, 43–65, 2014. [PDF]

Books

• Nakas, Bantis and Gatsonis. ROC Analysis for Classification and Prediction in Practice. CRC Press, 2023.
• Zhou, X.H. and Obuchowski, N.A. and McClish, D.K. Statistical Methods in Diagnostic Medicine. Wiley, New York, 2002.
• Pepe, M.S. The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford University Press, Oxford, 2003.
• Zou, Liu, Bandos, Ohno-Machado, Rockette. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis. Chapman and Hall/CRC, 2001. 
• Krzanowski, W.J.  and Hand, D.J.  ROC Curves for Continuous Data Chapman and Hall/CRC, 2009.