Premium
Smooth ROC curves and surfaces for markers subject to a limit of detection using monotone natural cubic splines
Author(s) -
Bantis Leonidas E.,
Tsimikas John V.,
Georgiou Stelios D.
Publication year - 2013
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201200158
Subject(s) - mathematics , limit (mathematics) , monotonic function , receiver operating characteristic , spline (mechanical) , monotone polygon , cumulative distribution function , statistics , mathematical analysis , geometry , probability density function , physics , thermodynamics
The use of ROC curves in evaluating a continuous or ordinal biomarker for the discrimination of two populations is commonplace. However, in many settings, marker measurements above or below a certain value cannot be obtained. In this paper, we study the construction of a smooth ROC curve (or surface in the case of three populations) when there is a lower or upper limit of detection. We propose the use of spline models that incorporate monotonicity constraints for the cumulative hazard function of the marker distribution. The proposed technique is computationally stable and simulation results showed a satisfactory performance. Other observed covariates can be also accommodated by this spline‐based approach.