Smooth time-dependent receiver operating characteristic curve estimators
Autor
Martínez-Camblor P.
Pardo-Fernández J.C.
Resumen
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. © 2017, © The Author(s) 2017.
Colecciones
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Article
Efficient nonparametric confidence bands for receiver operating-characteristic curves (2020)
Martínez-Camblor P.; Pérez-Fernández S.; Corral N. (SAGE Publications Ltd, 2018) -
Article
Factors affecting the validity of the oscillometric Ankle Brachial Index to detect peripheral arterial disease (2020)
Herráiz-Adillo Á.; Cavero-Redondo I.; Álvarez-Bueno C.; Martartínez-Vizcaíno V.; Pozuelo-Carrascosa D.P.; Notarnotario-Pacheco B. (Edizioni Minerva Medica, 2017) -
Article
Total and fetal circulating cell-free DNA, angiogenic, and antiangiogenic factors in preeclampsia and HELLP syndrome (2020)
Muñoz-Hernández R.; Medrano-Campillo P.; Miranda M.L.; Macher H.C.; Praena-Fernández J.M.; Vallejo-Vaz A.J.; Dominguez-Simeon M.J.; Moreno-Luna R.; Stiefel P. (Oxford University Press, 2017)