  Variable selection in high dimensional space has challenged many contemporary
statistical problems from many frontiers of scientific disciplines. Recent
technology advance has made it possible to collect a huge amount of covariate
information such as microarray, proteomic and SNP data via bioimaging
technology while observing survival information on patients in clinical
studies. Thus, the same challenge applies to the survival analysis in order to
understand the association between genomics information and clinical
information about the survival time. In this work, we extend the sure screening
procedure Fan and Lv (2008) to Cox's proportional hazards model with an
iterative version available. Numerical simulation studies have shown
encouraging performance of the proposed method in comparison with other
techniques such as LASSO. This demonstrates the utility and versatility of the
iterative sure independent screening scheme.
