The R Journal: article published in 2016, volume 8:2

easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment PDF download
Dincer Goksuluk, Selcuk Korkmaz, Gokmen Zararsiz and A. Ergun Karaagaoglu , The R Journal (2016) 8:2, pages 213-230.

Abstract ROC curve analysis is a fundamental tool for evaluating the performance of a marker in a number of research areas, e.g., biomedicine, bioinformatics, engineering etc., and is frequently used for discriminating cases from controls. There are a number of analysis tools which are used to guide researchers through their analysis. Some of these tools are commercial and provide basic methods for ROC curve analysis while others offer advanced analysis techniques and a command-based user interface, such as the R environment. The R environmentg includes comprehensive tools for ROC curve analysis; however, using a command-based interface might be challenging and time consuming when a quick evaluation is desired; especially for non-R users, physicians etc. Hence, a quick, comprehensive, free and easy-to-use analysis tool is required. For this purpose, we developed a user-friendly web tool based on the R language. This tool provides ROC statistics, graphical tools, optimal cutpoint calculation, comparison of several markers, and sample size estimation to support researchers in their decisions without writing R codes. easyROC can be used via any device with an internet connection independently of the operating system. The web interface of easyROC is constructed with the R package shiny. This tool is freely available through www.biosoft.hacettepe.edu.tr/easyROC.

Received: 2016-02-28; online 2016-12-23
CRAN packages: ROCR, pROC, OptimalCutpoints, shiny, plotROC, plyr , CRAN Task Views implied by cited CRAN packages: MachineLearning, Multivariate, WebTechnologies , Bioconductor packages: ROC


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@article{RJ-2016-042,
  author = {Dincer Goksuluk and Selcuk Korkmaz and Gokmen Zararsiz and
          A. Ergun Karaagaoglu},
  title = {{easyROC: An Interactive Web-tool for ROC Curve Analysis
          Using R Language Environment}},
  year = {2016},
  journal = {{The R Journal}},
  url = {https://journal.r-project.org/archive/2016/RJ-2016-042/index.html},
  pages = {213--230},
  volume = {8},
  number = {2}
}