scholarly journals Receiver operating characteristic curves and confidence bands for support vector machines

Biometrics ◽  
2020 ◽  
Author(s):  
Daniel J. Luckett ◽  
Eric B. Laber ◽  
Samer S. El‐Kamary ◽  
Cheng Fan ◽  
Ravi Jhaveri ◽  
...  
Keyword(s):  
Support Vector Machines ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Confidence Bands ◽  
Support Vector ◽  
Characteristic Curves ◽  
Receiver Operating Characteristic Curves ◽  
Vector Machines ◽  
Receiver Operating

A conditional approach for the receiver operating characteristic curve construction to evaluate diagnostic test performance in a family-matched case–control design

2021 ◽  
pp. 096228022199595
Author(s):  
Yalda Zarnegarnia ◽  
Shari Messinger
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Case Control ◽  
Paired Data ◽  
Characteristic Curves ◽  
Receiver Operating Characteristic Curves ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Receiver operating characteristic curves are widely used in medical research to illustrate biomarker performance in binary classification, particularly with respect to disease or health status. Study designs that include related subjects, such as siblings, usually have common environmental or genetic factors giving rise to correlated biomarker data. The design could be used to improve detection of biomarkers informative of increased risk, allowing initiation of treatment to stop or slow disease progression. Available methods for receiver operating characteristic construction do not take advantage of correlation inherent in this design to improve biomarker performance. This paper will briefly review some developed methods for receiver operating characteristic curve estimation in settings with correlated data from case–control designs and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using conditional receiver operating characteristic curves will be demonstrated. The proposed approach will use information about correlation among biomarker values, producing conditional receiver operating characteristic curves that evaluate the ability of a biomarker to discriminate between affected and unaffected subjects in a familial paired design.

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