bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests

Abstract Background Receiver operating characteristic (ROC) surface analysis is usually employed to assess the accuracy of a medical diagnostic test when there are three ordered disease status (e.g. non-diseased, intermediate, diseased). In practice, verification bias can occur due to missingness of...

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Main Author: Khanh To Duc
Format: Article
Language:English
Published: BMC 2017-11-01
Series:BMC Bioinformatics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12859-017-1914-3
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spelling doaj-85353d7c33ba435b93a4805bd44f19b72020-11-24T20:44:36ZengBMCBMC Bioinformatics1471-21052017-11-011811510.1186/s12859-017-1914-3bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic testsKhanh To Duc0Department of Statistical Sciences, University of PadovaAbstract Background Receiver operating characteristic (ROC) surface analysis is usually employed to assess the accuracy of a medical diagnostic test when there are three ordered disease status (e.g. non-diseased, intermediate, diseased). In practice, verification bias can occur due to missingness of the true disease status and can lead to a distorted conclusion on diagnostic accuracy. In such situations, bias–corrected inference tools are required. Results This paper introduce an R package, named bcROCsurface, which provides utility functions for verification bias–corrected ROC surface analysis. The shiny web application of the correction for verification bias in estimation of the ROC surface analysis is also developed. Conclusion bcROCsurface may become an important tool for the statistical evaluation of three–class diagnostic markers in presence of verification bias. The R package, readme and example data are available on CRAN. The web interface enables users less familiar with R to evaluate the accuracy of diagnostic tests, and can be found at http://khanhtoduc.shinyapps.io/bcROCsurface_shiny/ .http://link.springer.com/article/10.1186/s12859-017-1914-3SoftwareR packageROC surface analysisMissing at random
collection DOAJ
language English
format Article
sources DOAJ
author Khanh To Duc
spellingShingle Khanh To Duc
bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests
BMC Bioinformatics
Software
R package
ROC surface analysis
Missing at random
author_facet Khanh To Duc
author_sort Khanh To Duc
title bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests
title_short bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests
title_full bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests
title_fullStr bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests
title_full_unstemmed bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests
title_sort bcrocsurface: an r package for correcting verification bias in estimation of the roc surface and its volume for continuous diagnostic tests
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2017-11-01
description Abstract Background Receiver operating characteristic (ROC) surface analysis is usually employed to assess the accuracy of a medical diagnostic test when there are three ordered disease status (e.g. non-diseased, intermediate, diseased). In practice, verification bias can occur due to missingness of the true disease status and can lead to a distorted conclusion on diagnostic accuracy. In such situations, bias–corrected inference tools are required. Results This paper introduce an R package, named bcROCsurface, which provides utility functions for verification bias–corrected ROC surface analysis. The shiny web application of the correction for verification bias in estimation of the ROC surface analysis is also developed. Conclusion bcROCsurface may become an important tool for the statistical evaluation of three–class diagnostic markers in presence of verification bias. The R package, readme and example data are available on CRAN. The web interface enables users less familiar with R to evaluate the accuracy of diagnostic tests, and can be found at http://khanhtoduc.shinyapps.io/bcROCsurface_shiny/ .
topic Software
R package
ROC surface analysis
Missing at random
url http://link.springer.com/article/10.1186/s12859-017-1914-3
work_keys_str_mv AT khanhtoduc bcrocsurfaceanrpackageforcorrectingverificationbiasinestimationoftherocsurfaceanditsvolumeforcontinuousdiagnostictests
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