The covariate-adjusted ROC curve: the concept and its importance, review of inferential methods, and a new Bayesian estimator
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Publication:2092897
DOI10.1214/21-STS839OpenAlexW3194804976MaRDI QIDQ2092897
María Xosé Rodríguez-Álvarez, Vanda Inácio de Carvalho
Publication date: 4 November 2022
Published in: Statistical Science (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/journals/statistical-science/volume-37/issue-4/The-Covariate-Adjusted-ROC-Curve-The-Concept-and-Its/10.1214/21-STS839.full
receiver operating characteristic curvediagnostic testcovariate-adjustmentclassification accuracydecision thresholdDirichlet process (mixture) model
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- Adjusting for covariate effects on classification accuracy using the covariate-adjusted receiver operating characteristic curve
- ROC curve and covariates: extending induced methodology to the non-parametric framework
- The Analysis of Placement Values for Evaluating Discriminatory Measures
- R
- Understanding predictive information criteria for Bayesian models
- Comparative study of ROC regression techniques -- applications for the computer-aided diagnostic system in breast cancer detection
- Bayesian nonparametric ROC regression modeling
- A practical guide to splines
- Bias and efficiency loss due to categorizing an explanatory variable.
- A new flexible direct ROC regression model: application to the detection of cardiovascular risk factors by anthropometric measures
- A Bayesian analysis of some nonparametric problems
- Information borrowing methods for covariate-adjusted ROC curve
- ROC Curves in Non-Parametric Location-Scale Regression Models
- Statistical Methods in Diagnostic Medicine
- Selection and combination of biomarkers using ROC method for disease classification and prediction
- Bayesian Nonparametric Nonproportional Hazards Survival Modeling
- Inference for Mixtures of Finite Polya Tree Models
- A Predictive Approach to Model Selection
- Hazard Function Estimation Using B-Splines
- Nonparametric Bayesian covariate‐adjusted estimation of the Youden index
- Three Approaches to Regression Analysis of Receiver Operating Characteristic Curves for Continuous Test Results
- Gibbs Sampling Methods for Stick-Breaking Priors
- Bayesian Density Regression
- Matching in Studies of Classification Accuracy: Implications for Analysis, Efficiency, and Assessment of Incremental Value
- Combining Predictors for Classification Using the Area under the Receiver Operating Characteristic Curve
- Distribution-free ROC analysis using binary regression techniques
- Semi-parametric ROC regression analysis with placement values
- Order-Based Dependent Dirichlet Processes
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