Analysis of Survival Data with Group Lasso

DOI10.1080/03610918.2011.611311zbMath1270.62143OpenAlexW1997413230MaRDI QIDQ3168373

Insuk Sohn, Jinseog Kim, Changyi Park, Sujong Kim, Sin-Ho Jung

Publication date: 30 October 2012

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.611311

zbMATH Keywords

gene expressionsdiscrete covariate

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

Related Items

Identification of homogeneous and heterogeneous variables in pooled cohort studies, Variable selection with group LASSO approach: Application to Cox regression with frailty model, A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds, Counterfactual Explanation of Machine Learning Survival Models

Cites Work

• Microarray gene expression data with linked survival phenotypes: diffuse large-B-cell lymphoma revisited
• A group bridge approach for variable selection
• Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker
• Model Selection and Estimation in Regression with Grouped Variables