Risk prediction for prostate cancer recurrence through regularized estimation with simultaneous adjustment for nonlinear clinical effects

DOI10.1214/11-AOAS458zbMath1228.62142arXiv1111.5429OpenAlexW3101944101WikidataQ35539227 ScholiaQ35539227MaRDI QIDQ652366

Carlos S. Moreno, Qi Long, Brent A. Johnson, Matthias Chung

Publication date: 14 December 2011

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1111.5429

zbMATH Keywords

penalized splinesfeature selectionaccelerated failure time modellassorank estimationpartly linear model

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) General nonlinear regression (62J02) Medical applications (general) (92C50) Estimation in survival analysis and censored data (62N02)

Related Items (4)

A group bridge approach for component selection in nonparametric accelerated failure time additive regression model ⋮ Variable selection in partially linear additive hazards model with grouped covariates and a diverging number of parameters ⋮ Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic ⋮ Variable selection in high-dimensional partly linear additive models

Uses Software

• SemiPar

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