A leave-one-out cross-validation SAS macro for the identification of markers associated with survival

Comput Biol Med. 2015 Feb:57:123-9. doi: 10.1016/j.compbiomed.2014.11.015. Epub 2014 Dec 9.

Abstract

A proper internal validation is necessary for the development of a reliable and reproducible prognostic model for external validation. Variable selection is an important step for building prognostic models. However, not many existing approaches couple the ability to specify the number of covariates in the model with a cross-validation algorithm. We describe a user-friendly SAS macro that implements a score selection method and a leave-one-out cross-validation approach. We discuss the method and applications behind this algorithm, as well as details of the SAS macro.

Keywords: Clinical trials; Cross-validation; Prognostic markers; SAS macro; Score selection; Survival analysis.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Biomarkers*
  • Clinical Trials as Topic*
  • Computational Biology
  • Computer Simulation*
  • Humans
  • Prognosis*
  • Reproducibility of Results
  • Survival Analysis*

Substances

  • Biomarkers