A resampling-based test for two crossing survival curves

Pharm Stat. 2020 Jul;19(4):399-409. doi: 10.1002/pst.2000. Epub 2020 Jan 8.

Abstract

The area between two survival curves is an intuitive test statistic for the classical two-sample testing problem. We propose a bootstrap version of it for assessing the overall homogeneity of these curves. Our approach allows ties in the data as well as independent right censoring, which may differ between the groups. The asymptotic distribution of the test statistic as well as of its bootstrap counterpart are derived under the null hypothesis, and their consistency is proven for general alternatives. We demonstrate the finite sample superiority of the proposed test over some existing methods in a simulation study and illustrate its application by a real-data example.

Keywords: Kaplan-Meier estimator; Wilcoxon test; area between curves; conditional bootstrap test; log-rank test; nonproportional hazard.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Catheterization
  • Computer Simulation
  • Humans
  • Models, Statistical*
  • Renal Dialysis / mortality*
  • Survival Rate