Literature DB >> 3841685

An evaluation of methods for estimating the area under the receiver operating characteristic (ROC) curve.

R M Centor, J S Schwartz.   

Abstract

The area under the receiver operating characteristic (ROC) curve serves as one means for evaluating the performance of diagnostic and predictive test systems. The most commonly used method for estimating the area under an ROC curve utilizes the maximum-likelihood-estimation technique, and a nonparametric method to calculate the area under an ROC curve was recently described. We compared the performance of these two methods. The results for the area under the ROC curve and the standard error of the estimate as calculated by each of the two methods exhibited high correlation. Generally, the nonparametric method yields lower area estimates than the maximum-likelihood-estimation technique. However, these differences generally were small, particularly with ROC curves derived from five or more cutoff points. Consistent results of hypothesis testing of the significance of differences between two ROC curves will be similar, regardless of which method is used, as long as one uses the same estimation technique on the two curves and as long as the two ROC curves being compared are of similar shape.

Mesh:

Year:  1985        PMID: 3841685     DOI: 10.1177/0272989X8500500204

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  21 in total

1.  Regionalized GC content of template DNA as a predictor of PCR success.

Authors:  Yair Benita; Ronald S Oosting; Martin C Lok; Michael J Wise; Ian Humphery-Smith
Journal:  Nucleic Acids Res       Date:  2003-08-15       Impact factor: 16.971

2.  Comparison of algorithm advice for post-acute care referral to usual clinical decision-making: examination of 30-day acute healthcare utilization.

Authors:  Susan K Keim; Kathryn H Bowles
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

3.  A critical assessment of clinical diagnosis of disc herniation in patients with monoradicular sciatica.

Authors:  M J Albeck
Journal:  Acta Neurochir (Wien)       Date:  1996       Impact factor: 2.216

4.  Clinical decision analysis using microcomputers. A case of coexistent hepatocellular carcinoma and abdominal aortic aneurysm.

Authors:  J B Wong; A J Moskowitz; S G Pauker
Journal:  West J Med       Date:  1986-12

5.  SenseWearMini and Actigraph GT3X Accelerometer Classification of Observed Sedentary and Light-Intensity Physical Activities in a Laboratory Setting.

Authors:  Lynne M Feehan; Charles H Goldsmith; April Y F Leung; Linda C Li
Journal:  Physiother Can       Date:  2016       Impact factor: 1.037

6.  CT and MR assessment of tumors of the nose and paranasal sinuses, the nasopharynx and the parapharyngeal space using ROC methodology.

Authors:  M G Hunink; R G de Slegte; G J Gerritsen; H Speelman
Journal:  Neuroradiology       Date:  1990       Impact factor: 2.804

7.  Biochemical tests for pheochromocytoma: strategies in hypertensive patients.

Authors:  M J Young; C Dmuchowski; J W Wallis; G P Barnas; B Shapiro
Journal:  J Gen Intern Med       Date:  1989 Jul-Aug       Impact factor: 5.128

8.  Rapid classification of positive blood cultures: validation and modification of a prediction model.

Authors:  S Ram; J M Mylotte; M Pisano
Journal:  J Gen Intern Med       Date:  1995-02       Impact factor: 5.128

9.  Prevalence of metacarpal osteopenia in young rheumatoid arthritis patients.

Authors:  A A Kalla; O L Meyers; R Laubscher
Journal:  Clin Rheumatol       Date:  1995-11       Impact factor: 2.980

10.  Hospital readmission in general medicine patients: a prediction model.

Authors:  Omar Hasan; David O Meltzer; Shimon A Shaykevich; Chaim M Bell; Peter J Kaboli; Andrew D Auerbach; Tosha B Wetterneck; Vineet M Arora; James Zhang; Jeffrey L Schnipper
Journal:  J Gen Intern Med       Date:  2009-12-15       Impact factor: 5.128

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