Nonparametric Cutoff Point Estimation for Diagnostic Decisions with Weighted Errors

被引:0
|
作者
Martinez-Camblor, Pablo [1 ,2 ]
机构
[1] CAIBER, Oficina Invest Biosanitaria, Oviedo, Spain
[2] Univ Oviedo, Dept Estadist & IO & DM, Oviedo, Spain
来源
REVISTA COLOMBIANA DE ESTADISTICA | 2011年 / 34卷 / 01期
关键词
Kernel density estimator; Sensitivity; Specificity; Threshold; Utility function;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The study of diagnostic tests is a hot topic which has direct applications in biomedical sciences. Despite of the relevance, in a diagnostic process, of the threshold (or cutoff point) employed on the decision taken by the physician, the study and comparison of the accuracy among different diagnostic criterions has been the main field of study. In this paper, the authors are interested in the study of the involved cutoff point estimation in diagnostic tests with weighted errors. With this goal, a nonparametric smoothed utility function estimator is considered. The bootstrap and the asymptotic distributions for the related M-estimator are derived. Finally, the obtained results are applied to study the Procalcitonin level which determines whether a child within the Pediatric Intensive Care Unit (UCIP) has a virical sepsis.
引用
收藏
页码:133 / 146
页数:14
相关论文
共 50 条