Literature DB >> 8858790

A simple method for comparing correlated ROC curves using incomplete data.

X H Zhou1, C A Gatsonis.   

Abstract

Comparative studies of the accuracy of diagnostic procedures often use a paired design to gain in efficiency. Standard methods for analysing data from paired designs require complete observations. In many studies, however, one of the test results may be missing for some patients. In this paper, we propose a simple correction to the existing complete data methods to compare areas under ROC curves derived from paired designs. The approach makes it possible to use the entire available data set in carrying out the comparison, provided that the probability of having both tests does not depend on the test results. As an illustration, we apply our method to the analysis of data from prospective comparison of MRI and ultrasound in detecting periprostatic invasion.

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Year:  1996        PMID: 8858790     DOI: 10.1002/(SICI)1097-0258(19960815)15:15<1687::AID-SIM324>3.0.CO;2-S

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  8 in total

Review 1.  ROC analysis in medical imaging: a tutorial review of the literature.

Authors:  Charles E Metz
Journal:  Radiol Phys Technol       Date:  2007-10-27

2.  A new quality assessment parameter for optical coherence tomography.

Authors:  D M Stein; H Ishikawa; R Hariprasad; G Wollstein; R J Noecker; J G Fujimoto; J S Schuman
Journal:  Br J Ophthalmol       Date:  2006-02       Impact factor: 4.638

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

Authors:  Leonidas E Bantis; Ziding Feng
Journal:  Stat Med       Date:  2016-06-20       Impact factor: 2.373

4.  Power calculation for comparing diagnostic accuracies in a multi-reader, multi-test design.

Authors:  Eunhee Kim; Zheng Zhang; Youdan Wang; Donglin Zeng
Journal:  Biometrics       Date:  2014-10-29       Impact factor: 2.571

5.  Bivariate marker measurements and ROC analysis.

Authors:  Mei-Cheng Wang; Shanshan Li
Journal:  Biometrics       Date:  2012-09-24       Impact factor: 2.571

6.  Improving Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for Digital Breast Tomosynthesis.

Authors:  Emily F Conant; Alicia Y Toledano; Senthil Periaswamy; Sergei V Fotin; Jonathan Go; Justin E Boatsman; Jeffrey W Hoffmeister
Journal:  Radiol Artif Intell       Date:  2019-07-31

7.  A statistical framework to evaluate virtual screening.

Authors:  Wei Zhao; Kirk E Hevener; Stephen W White; Richard E Lee; James M Boyett
Journal:  BMC Bioinformatics       Date:  2009-07-20       Impact factor: 3.169

8.  Quantitative Analysis of a Whole Cardiac Mass Using Dual-Energy Computed Tomography: Comparison with Conventional Computed Tomography and Magnetic Resonance Imaging.

Authors:  Yoo Jin Hong; Jin Hur; Kyunghwa Han; Dong Jin Im; Young Joo Suh; Hye-Jeong Lee; Young Jin Kim; Byoung Wook Choi
Journal:  Sci Rep       Date:  2018-10-18       Impact factor: 4.379

  8 in total

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