Comparison of two correlated ROC curves at a given specificity or sensitivity level

Nonparametric Methods in Comparing Two Correlated Roc Curves

Receiver Operating Characteristic (ROC) analysis is one of the most widely used methods for summarizing intrinsic properties of a diagnostic system, and is often used in evaluation and comparison of diagnostic technologies, practices or systems. These methods play an important role in public health since they enable researchers to achieve a greater insight into the properties of diagnostic test...

Regression Analysis for Correlated ROC Curves

1 Sensitivity , Specificity , Accuracy , Associated Confidence Interval and ROC

Diagnosis tests include different kinds of information, such as medical tests (e.g. blood tests, X-rays, MRA), medical signs (clubbing of the fingers, a sign of lung disease), or symptoms (e.g. pain in a particular pattern). Doctor’s decisions of medical treatment rely on diagnosis tests, which makes the accuracy of a diagnosis is essential in medical care. Fortunately, the attributes of the di...

Statistical comparison of ROC curves from multiple readers.

Receiver operating characteristic (ROC) analysis is the commonly accepted method for comparing diagnostic imaging systems. In general, ROC studies are designed in such a way that multiple readers read the same images and each image is presented by means of two different imaging systems. Statistical methods for the comparison of the ROC curves from one reader have been developed, but extension o...

Resampling ROC curves

Receiver operating characteristic (ROC) curves are very popular for evaluating a diagnostic test or score performances in various decision making applications: medicine, marketing, credit scoring etc. The ROC curve provides a concise graphical representation of the trade off between sensitivity and specificity. We will focus here on supervised classification into two groups. Error rate estimati...