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Abstract Many modern biomedical studies have yielded survival data with high-throughput
predictors. The goals of scientific research often lie in identifying predictive biomarkers, understanding
biological mechanisms and making accurate and precise predictions. Variable screening
is a crucial first step in achieving these goals. This work conducts a selective review of feature
screening procedures for survival data with ultrahigh dimensional covariates. We present the
main methodologies, along with the key conditions that ensure sure screening properties. The
practical utility of these methods is examined via extensive simulations. We conclude the review
with some future opportunities in this field.
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Published: 27 December 2017
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