scholarly journals A Computer Program for Rapid Generation of Receiver Operating Characteristic Curves and Likelihood Ratios in the Evaluation of Diagnostic Tests

1989 ◽  
Vol 26 (2) ◽  
pp. 210-210
Author(s):  
A C J Hutchesson
Keyword(s):  
Computer Program ◽  
Receiver Operating Characteristic ◽  
Diagnostic Tests ◽  
Operating Characteristic ◽  
Likelihood Ratios ◽  
Characteristic Curves ◽  
Receiver Operating Characteristic Curves ◽  
Rapid Generation ◽  
Receiver Operating

scholarly journals Tree-structured Subgroup Analysis of Receiver Operating Characteristic Curves for Diagnostic Tests

2012 ◽  
Vol 19 (12) ◽  
pp. 1529-1536 ◽  
Author(s):  
Caixia Li ◽  
Claus-C. Glüer ◽  
Richard Eastell ◽  
Dieter Felsenberg ◽  
David M. Reid ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Subgroup Analysis ◽  
Diagnostic Tests ◽  
Operating Characteristic ◽  
Characteristic Curves ◽  
Receiver Operating Characteristic Curves ◽  
Receiver Operating

A Computer Program for Rapid Generation of Receiver Operating Characteristic Curves and Likelihood Ratios in the Evaluation of Diagnostic Tests

1988 ◽  
Vol 25 (4) ◽  
pp. 411-416 ◽  
Author(s):  
Thomas G Pellar ◽  
Fred Y Leung ◽  
A Ralph Henderson
Keyword(s):  
Receiver Operating Characteristic ◽  
Frequency Distribution ◽  
Operating Characteristic ◽  
Roc Curves ◽  
Likelihood Ratios ◽  
Receiver Operating Characteristic Curves ◽  
Data Files ◽  
Rapid Generation ◽  
Distribution Sensitivity ◽  
Receiver Operating

We describe a MUMPS program to facilitate the evaluation of the diagnostic effectiveness and efficiency of laboratory tests using receiver operating characteristic (ROC) curves and likelihood ratios (LR). Test results from a population with and without a disease are stored into retrievable, editable data bases. Either single or a combination (≤9) of different test data files can be accessed to generate tables of calculated frequency distribution, sensitivity, 1-specificity and LR at variable decision thresholds. The program also calculates the area under the ROC curve, confidence intervals and SE. The selection of the optimum cut-off value is assisted by graphical plots of frequency distribution, ROC and decision level curves as illustrated by using some ‘cardiac’ enzyme tests.

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