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Marginal variable screening for survival endpoints.

Dominic EdelmannManuela HummelThomas HielscherMaral SaadatiAxel Benner
Published in: Biometrical journal. Biometrische Zeitschrift (2019)
When performing survival analysis in very high dimensions, it is often required to reduce the number of covariates using preliminary screening. During the last years, a large number of variable screening methods for the survival context have been developed. However, guidance is missing for choosing an appropriate method in practice. The aim of this work is to provide an overview of marginal variable screening methods for survival and develop recommendations for their use. For this purpose, a literature review is given, offering a comprehensive and structured introduction to the topic. In addition, a novel screening procedure based on distance correlation and martingale residuals is proposed, which is particularly useful in detecting nonmonotone associations. For evaluating the performance of the discussed approaches, a simulation study is conducted, comparing the true positive rates of competing variable screening methods in different settings. A real data example on mantle cell lymphoma is provided.
Keyphrases
  • healthcare
  • primary care
  • free survival
  • deep learning
  • quality improvement