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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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 |
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English |
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Article |
sources |
DOAJ |
author |
Khanh To Duc |
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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 |
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Khanh To Duc |
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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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1716816842909024256 |