A regression approach to ROC surface, with applications to Alzheimer's disease

DOI10.1007/s11425-012-4462-3zbMath1258.62052OpenAlexW1976424051WikidataQ37498051 ScholiaQ37498051MaRDI QIDQ1933976

Jason P. Fine, Jia-Liang Li, Xiao-Hua Andrew Zhou

Publication date: 28 January 2013

Published in: Science China. Mathematics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3897001

zbMATH Keywords

bootstrapmaximum likelihood estimationrank regressiontransformation modelreceiver operating characteristic surfacevolume under ROC surface

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (3)

Estimation of the volume under a ROC surface in presence of covariates ⋮ The generalized Lehmann ROC curves: Lehmann family of ROC surfaces ⋮ Hypervolume under ROC manifold for discrete biomarkers with ties

Uses Software

• S-PLUS
• MEMSS

Cites Work

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• Adjusting for covariate effects on classification accuracy using the covariate-adjusted receiver operating characteristic curve
• ROC analysis with multiple classes and multiple tests: methodology and its application in microarray studies
• Nonparametric and semiparametric estimation of the three way receiver operating characteristic surface
• A non-parametric analysis of transformations
• COMBINING MULTIPLE MARKERS FOR MULTI-CATEGORY CLASSIFICATION: AN ROC SURFACE APPROACH
• Efficient Instrumental Variables Estimation of Nonlinear Models
• Best Nonlinear Three-Stage Least Squares Estimation of Certain Econometric Models
• Likelihood Methods and Nonparametric Tests
• Miscellanea. On the linear transformation model for censored data
• Rank-based inference for the accelerated failure time model
• Estimation for the Box-Cox Transformation Model Without Assuming Parametric Error Distribution
• Mixed-Effects Models in S and S-PLUS
• Nonparametric Estimation of the Transformation in the Transform-Both-Sides Regression Model
• Analysing Competing Risks Data With Transformation Models
• Confidence interval for the bootstrapP-value and sample size calculation of the bootstrap test

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