Work

A Two-Stage Feature Screening Framework for Ultrahigh-Dimensional Survival Data

Year: 2025

Type: article

Abstract: Identifying important features associated with right-censored survival time in ultrahigh-dimensional survival data is a challenging task due to the curse of dimensionality and information loss caused by censoring. To address these challenges, we propose a two-stage feature screening framework consisting of an imputation step and a feature screening step. The use of Buckley–James imputation leverages information from censoring and can therefore enhance the overall screening performance, particularly when the censoring rate is relatively high. We establish the sure screening properties of the two screening procedures proposed under this framework and illustrate their advantages through simulations. A real-world example is also provided to demonstrate the practical usefulness of the proposed approach.

Source: Mathematics

DOI: 10.3390/math14010093

Authors: Xinyi Min, Wenbo Wu, Baoying Yang

Institutions: Southwest Jiaotong University, The University of Texas at San Antonio

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,137