Premium
Statistical inference for the difference between two maximized Youden indices obtained from correlated biomarkers
Author(s) -
Bantis Leonidas E.,
Nakas Christos T.,
Reiser Benjamin
Publication year - 2021
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.202000128
Subject(s) - youden's j statistic , receiver operating characteristic , nonparametric statistics , statistics , mathematics , inference , kernel (algebra) , kernel density estimation , confidence interval , cutoff , parametric statistics , complement (music) , statistical inference , pattern recognition (psychology) , artificial intelligence , computer science , biology , biochemistry , physics , combinatorics , quantum mechanics , estimator , complementation , gene , phenotype
Currently, there is global interest in deriving new promising cancer biomarkers that could complement or substitute the conventional ones. Clinical decisions can often be based on the cutoff that corresponds to the maximized Youden index when maximum accuracy drives decisions. When more than one classification criteria are measured within the same individuals, correlated measurements arise. In this work, we propose hypothesis tests and confidence intervals for the comparison of two correlated receiver operating characteristic (ROC) curves in terms of their corresponding maximized Youden indices. We explore delta‐based techniques under parametric assumptions, or power transformations. Nonparametric kernel‐based methods are also examined. We evaluate our approaches through simulations and illustrate them using data from a metabolomic study referring to the detection of pancreatic cancer.