Literature DB >> 8412547

Confidence bands for receiver operating characteristic curves.

G Ma1, W J Hall.   

Abstract

Receiver operating characteristic (ROC) curves are mapped out by the two types of errors that are generated by varying the decision threshold used to determine which subjects will be considered abnormal. Under the conventional binormal model for the ROC curve, two-sided and one-sided simultaneous confidence bands for an entire ROC curve, or for a portion of an ROC curve, are constructed by employing Working-Hotelling-type confidence bands for simple linear regression. Pointwise confidence bands are presented for comparison. The cases in which one has only asymptotically normally distributed estimates of the parameters of the ROC curve and consistent estimates of their variance-covariance matrix are emphasized. The methods extend beyond binormal models.

Mesh:

Year:  1993        PMID: 8412547     DOI: 10.1177/0272989X9301300304

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


  9 in total

1.  Confidence intervals for performance assessment of linear observers.

Authors:  Adam Wunderlich; Frédéric Noo
Journal:  Med Phys       Date:  2011-07       Impact factor: 4.071

2.  Confidence intervals and bands for the binormal ROC curve revisited.

Authors:  Eugene Demidenko
Journal:  J Appl Stat       Date:  2011-12-12       Impact factor: 1.404

3.  Radiation dose prediction using data on time to emesis in the case of nuclear terrorism.

Authors:  Eugene Demidenko; Benjamin B Williams; Harold M Swartz
Journal:  Radiat Res       Date:  2009-03       Impact factor: 2.841

4.  Adjustment for measurement error in evaluating diagnostic biomarkers by using an internal reliability sample.

Authors:  Matthew T White; Sharon X Xie
Journal:  Stat Med       Date:  2013-06-14       Impact factor: 2.373

5.  Receiver operating characteristic curves and confidence bands for support vector machines.

Authors:  Daniel J Luckett; Eric B Laber; Samer S El-Kamary; Cheng Fan; Ravi Jhaveri; Charles M Perou; Fatma M Shebl; Michael R Kosorok
Journal:  Biometrics       Date:  2020-09-12       Impact factor: 1.701

6.  Diagnostic Utility of Gene Expression Profiles.

Authors:  Chengjie Xiong; Yan Yan; Feng Gao
Journal:  J Biom Biostat       Date:  2013-01-04

7.  Neyman-Pearson classification algorithms and NP receiver operating characteristics.

Authors:  Xin Tong; Yang Feng; Jingyi Jessica Li
Journal:  Sci Adv       Date:  2018-02-02       Impact factor: 14.136

8.  Assessing the statistical significance of the achieved classification error of classifiers constructed using serum peptide profiles, and a prescription for random sampling repeated studies for massive high-throughput genomic and proteomic studies.

Authors:  James Lyons-Weiler; Richard Pelikan; Herbert J Zeh; David C Whitcomb; David E Malehorn; William L Bigbee; Milos Hauskrecht
Journal:  Cancer Inform       Date:  2005

9.  Temperature differences are associated with malignancy on lung lesions: a clinical study.

Authors:  Christodoulos Stefanadis; Christina Chrysohoou; Demosthenes B Panagiotakos; Elisabeth Passalidou; Vasiliki Katsi; Vlassios Polychronopoulos; Pavlos K Toutouzas
Journal:  BMC Cancer       Date:  2003-01-06       Impact factor: 4.430

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.