1 Department of Biomedical Data Science, The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, USA.
2 Universidad Autonoma de Chile, Santiago, Chile.
Stat Methods Med Res. 2018 Jun;27(6):1892-1908. doi: 10.1177/0962280216672490. Epub 2016 Oct 17.
Receiver operating-characteristic curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous (bio)markers. In spite of the existence of a huge number of papers devoted to both theoretical and practical aspects of this topic, the construction of confidence bands has had little impact in the specialized literature. As far as the authors know, in the CRAN there are only three R packages providing receiver operating-characteristic curve confidence regions: plotROC, pROC and fbroc. This work tries to fill this gap studying and proposing a new nonparametric method to build confidence bands for both the standard receiver operating-characteristic curve and its generalization for nonmonotone relationships. The behavior of the proposed procedure is studied via Monte Carlo simulations and the methodology is applied on two real-world biomedical problems. In addition, an R function to compute the proposed and some of the previously existing methodologies is provided as online supplementary material.
受试者工作特征曲线是一种常用的图形方法，常用于研究连续（生物）标志物的诊断能力。尽管已经有大量的论文致力于该主题的理论和实际方面，但置信带的构建在专业文献中影响甚微。据作者所知，在 CRAN 中，只有三个 R 包提供了受试者工作特征曲线置信区间：plotROC、pROC 和 fbroc。这项工作试图通过研究和提出一种新的非参数方法来填补这一空白，为标准受试者工作特征曲线及其对非单调关系的推广构建置信带。通过蒙特卡罗模拟研究了所提出方法的行为，并将该方法应用于两个真实的生物医学问题。此外，还提供了一个 R 函数来计算所提出的方法和一些以前存在的方法，作为在线补充材料。
