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Marginal variable screening for survival endpoints
Author(s) -
Edelmann Dominic,
Hummel Manuela,
Hielscher Thomas,
Saadati Maral,
Benner Axel
Publication year - 2020
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201800269
Subject(s) - covariate , variable (mathematics) , computer science , martingale (probability theory) , context (archaeology) , statistics , econometrics , data mining , mathematics , machine learning , mathematical analysis , paleontology , biology
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.