Model-free Feature Screening via Revised Chatterjee's Rank Correlation for Ultra-high Dimensional Censored Data

2026-03-27

AI Summary

This study addresses the lack of model-free and computationally efficient feature screening methods for ultra-high-dimensional right-censored survival data. It introduces, for the first time in this context, a screening approach based on the modified Chatterjee rank correlation, which does not rely on any specific survival model assumption. Built upon rank statistics, the proposed method combines computational simplicity with strong theoretical consistency and is applicable across a broad class of censored survival models. Extensive simulations and real-data analyses using gene expression profiles demonstrate that the method achieves superior screening performance and robustness, significantly advancing model-free feature screening for ultra-high-dimensional survival data.

Technology Category

Machine Learning: Dimensionality Reduction/Feature SelectionReasoning under Uncertainty: Graphical ModelsData Mining & Knowledge Management: Mining of Visual, Multimedia & Multimodal Data

Application Category

Search and Retrieval-Augmented AI: Web search models and rankingUser Modeling, Personalization and Recommendation: Fairness-aware retrieval and rankingGraph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs

Abstract

In large-scale biomedical research, it's common to gather ultra-high dimensional data that includes right-censored survival times. Feature screening has emerged as a crucial statistical technique for handling such data. In this paper, we introduce a straightforward and robust feature screening approach, leveraging the modified Chatterjee's rank correlation, suitable for a broad range of survival models. With reasonably mild regularity assumptions, we establish the properties of sure screening and ranking consistency. The computation involved in our proposed method is quite direct and simple. Through simulation studies and real gene expression data analysis, we demonstrate the superior efficacy of our proposed approach.

Problem

• feature screening
• ultra-high dimensional data
• right-censored survival data
• Chatterjee's rank correlation

Innovation

• model-free
• feature screening
• Chatterjee's rank correlation
• ultra-high dimensional
• censored data