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Smooth time-dependent receiver operating characteristic curve estimators.
- Source :
- Statistical Methods in Medical Research; Mar2018, Vol. 27 Issue 3, p651-674, 24p
- Publication Year :
- 2018
-
Abstract
- The receiver operating characteristic curve is a popular graphical method often used to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, two main extensions have been proposed: the cumulative/dynamic receiver operating characteristic curve and the incident/dynamic receiver operating characteristic curve. In both cases, the main problem for developing appropriate estimators is the estimation of the joint distribution of the variables time-to-event and marker. As usual, different approximations lead to different estimators. In this article, the authors explore the use of a bivariate kernel density estimator which accounts for censored observations in the sample and produces smooth estimators of the time-dependent receiver operating characteristic curves. The performance of the resulting cumulative/dynamic and incident/dynamic receiver operating characteristic curves is studied by means of Monte Carlo simulations. Additionally, the influence of the choice of the required smoothing parameters is explored. Finally, two real-applications are considered. An R package is also provided as a complement to this article. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09622802
- Volume :
- 27
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Statistical Methods in Medical Research
- Publication Type :
- Academic Journal
- Accession number :
- 128167872
- Full Text :
- https://doi.org/10.1177/0962280217740786