Cumulative/dynamic ROC curve estimation

Receiver operating-characteristic (ROC) curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, the direct generalization is known as cumulative/dynamic ROC curve. For a fixed...

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Published inJournal of statistical computation and simulation Vol. 86; no. 17; pp. 3582 - 3594
Main Authors Martínez-Camblor, Pablo, Bayón, Gustavo F., Pérez-Fernández, Sonia
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 21.11.2016
Taylor & Francis Ltd
Subjects
Approximation
censored data
Censorship
Computer simulation
Cox regression model
Cumulative/dynamic ROC curve
Diagnostic systems
Dynamics
Estimators
Mathematical analysis
Monte Carlo simulation
Receivers
sensitivity
Sensitivity analysis
specificity
Time dependence
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Abstract Receiver operating-characteristic (ROC) curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, the direct generalization is known as cumulative/dynamic ROC curve. For a fixed point of time, t, one subject is allocated into the positive group if the event happens before t and into the negative group if the event is not happened at t. The presence of censored subject, which can not be directly assigned into a group, is the main handicap of this approach. The proposed cumulative/dynamic ROC curve estimator assigns a probability to belong to the negative (positive) group to the subjects censored previously to t. The performance of the resulting estimator is studied from Monte Carlo simulations. Some real-world applications are reported. Results suggest that the new estimators provide a good approximation to the real cumulative/dynamic ROC curve.
AbstractList Receiver operating-characteristic (ROC) curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, the direct generalization is known as cumulative/dynamic ROC curve. For a fixed point of time, t, one subject is allocated into the positive group if the event happens before t and into the negative group if the event is not happened at t. The presence of censored subject, which can not be directly assigned into a group, is the main handicap of this approach. The proposed cumulative/dynamic ROC curve estimator assigns a probability to belong to the negative (positive) group to the subjects censored previously to t. The performance of the resulting estimator is studied from Monte Carlo simulations. Some real-world applications are reported. Results suggest that the new estimators provide a good approximation to the real cumulative/dynamic ROC curve.
Receiver operating-characteristic (ROC) curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, the direct generalization is known as cumulative/dynamic ROC curve. For a fixed point of time, t, one subject is allocated into the positive group if the event happens before t and into the negative group if the event is not happened at t. The presence of censored subject, which can not be directly assigned into a group, is the main handicap of this approach. The proposed cumulative/dynamic ROC curve estimator assigns a probability to belong to the negative (positive) group to the subjects censored previously to t. The performance of the resulting estimator is studied from Monte Carlo simulations. Some real-world applications are reported. Results suggest that the new estimators provide a good approximation to the real cumulative/dynamic ROC curve.
Author Bayón, Gustavo F.
Martínez-Camblor, Pablo
Pérez-Fernández, Sonia
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Snippet Receiver operating-characteristic (ROC) curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous...
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SubjectTerms Approximation
censored data
Censorship
Computer simulation
Cox regression model
Cumulative/dynamic ROC curve
Diagnostic systems
Dynamics
Estimators
Mathematical analysis
Monte Carlo simulation
Receivers
sensitivity
Sensitivity analysis
specificity
Time dependence
Title Cumulative/dynamic ROC curve estimation
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