Lifetime Data Analysis

, Volume 23, Issue 4, pp 671–691 | Cite as

\(L_1\) splitting rules in survival forests

  • Hoora Moradian
  • Denis LarocqueEmail author
  • François Bellavance


The log-rank test is used as the split function in many commonly used survival trees and forests algorithms. However, the log-rank test may have a significant loss of power in some circumstances, especially when the hazard functions or when the survival functions cross each other in the two compared groups. We investigate the use of the integrated absolute difference between the two children nodes survival functions as the splitting rule. Simulations studies and applications to real data sets show that forests built with this rule produce very good results in general, and that they are often better compared to forests built with the log-rank splitting rule.


Survival data Right-censored data Ensemble methods Random forests Survival forests 



The authors would like to thank the Associate Editor and two reviewers whose comments helped in preparing an improved version of this article. This research was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and by Le Fonds québécois de la recherche sur la nature et les technologies (FQRNT).

Supplementary material

10985_2016_9372_MOESM1_ESM.pdf (224 kb)
Supplementary material 1 (pdf 223 KB)


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Hoora Moradian
    • 1
  • Denis Larocque
    • 1
    Email author
  • François Bellavance
    • 1
  1. 1.Department of Decision SciencesHEC MontréalMontrealCanada

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