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Marginal variable screening for survival endpoints.

Dominic Edelmann1, Manuela Hummel1, Thomas Hielscher1

  • 1Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Biometrical Journal. Biometrische Zeitschrift
|August 27, 2019
PubMed
Summary
This summary is machine-generated.

This study reviews marginal variable screening methods for high-dimensional survival analysis and proposes a new procedure. Recommendations are provided to guide the selection of appropriate screening techniques in practice.

Keywords:
distance correlationhigh dimensionsmethods overviewsurvivalvariable screening

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Area of Science:

  • Biostatistics
  • Statistical genetics
  • Bioinformatics

Background:

  • High-dimensional survival analysis often requires covariate reduction via preliminary screening.
  • Numerous variable screening methods for survival data have emerged, yet practical guidance is lacking.
  • Choosing the right screening method is crucial for effective analysis.

Purpose of the Study:

  • To provide a comprehensive overview of marginal variable screening methods for survival analysis.
  • To develop practical recommendations for selecting appropriate screening methods.
  • To introduce a novel screening procedure for detecting non-monotone associations.

Main Methods:

  • Literature review of existing marginal variable screening methods.
  • Development of a new screening procedure utilizing distance correlation and martingale residuals.
  • Simulation study to evaluate and compare the performance (true positive rates) of different screening methods.

Main Results:

  • A structured overview of marginal variable screening methods is presented.
  • The proposed novel screening procedure demonstrates utility in detecting non-monotone associations.
  • Simulation results compare the effectiveness of various screening methods across different scenarios.

Conclusions:

  • The work offers guidance for practitioners in selecting variable screening methods for survival analysis.
  • The novel distance correlation and martingale residual-based method provides a valuable addition for identifying complex relationships.
  • The findings aid in improving the efficiency and accuracy of high-dimensional survival data analysis.