A computer program for non-parametric receiver operating characteristic analysis.

Sensitivity and specificity are key measures of the performance of a given test in detecting a given disorder. For tests yielding numerical scores, sensitivity and specificity usually vary inversely over the range of theoretically possible cutoff scores, complicating the task of quantifying and comparing the diagnostic accuracy of tests. Receiver Operating Characteristic analysis (ROC) approaches this problem by plotting the curve of sensitivity versus 1-specificity for all possible cutoff scores of the test. The area under the ROC curve (AUC) can be used to describe the diagnostic accuracy of the test. Parametric and non-parametric methods exist that allow the calculation of the AUC and the comparison of tests. A disadvantage of parametric formulations is the assumption of a normal or Gaussian distribution of test scores. The present article presents a computer program that utilizes non-parametric formulations that do not require the normal distribution of test scores. The program calculates the sensitivity and specificity of a test at all possible cutoff scores, plots the ROC curve, calculates the AUC, its standard error and 95% confidence limits, and allows the comparison of tests on independent and correlated samples.

[1]  D Mossman,et al.  Maximizing diagnostic information from the dexamethasone suppression test. An approach to criterion selection using receiver operating characteristic analysis. , 1989, Archives of general psychiatry.

[2]  F de Waard,et al.  Analysis of the diagnostic performance in breast cancer screening by relative operating characteristics , 1986, Cancer.

[3]  J. Swets ROC analysis applied to the evaluation of medical imaging techniques. , 1979, Investigative radiology.

[4]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[5]  E. DeLong,et al.  Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. , 1988, Biometrics.

[6]  C. Metz Basic principles of ROC analysis. , 1978, Seminars in nuclear medicine.

[7]  M C Weinstein,et al.  Performance of screening and diagnostic tests. Application of receiver operating characteristic analysis. , 1987, Archives of general psychiatry.

[8]  L B Lusted,et al.  Radiographic applications of receiver operating characteristic (ROC) curves. , 1974, Radiology.

[9]  J J Bartko,et al.  Diagnosing diagnoses. Receiver operating characteristic methods and psychiatry. , 1989, Archives of general psychiatry.

[10]  J R Beck,et al.  The use of relative operating characteristic (ROC) curves in test performance evaluation. , 1986, Archives of pathology & laboratory medicine.

[11]  W. Burke,et al.  Use of the Geriatric Depression Scale in Dementia of the Alzheimer Type , 1989, Journal of the American Geriatrics Society.

[12]  D. Bamber The area above the ordinal dominance graph and the area below the receiver operating characteristic graph , 1975 .