A1956
Title: Model-free feature screening via revised Chatterjee's rank correlation for ultra-high dimensional censored data
Authors: Shuya Chen - Beijing Normal-Hong Kong Baptist University (China) [presenting]
Min Zhou - Beijing Normal-Hong Kong Baptist University (China)
Heng Peng - Hong Kong Baptist Unversity (Hong Kong)
Abstract: In large-scale biomedical research, ultra-high dimensional data with right-censored survival times are commonly gathered. Feature screening has emerged as a crucial statistical technique for handling such data. A straightforward and robust feature screening approach leveraging the modified Chatterjee's rank correlation is introduced, suitable for a broad range of survival models. With reasonably mild regularity assumptions, sure screening properties and ranking consistency are established. The computation involved in the proposed method is direct and simple. Simulation studies and real gene expression data analysis demonstrate the superior efficacy of the proposed approach.
