Statistical Methods for Conditional Survival Analysis

J Biopharm Stat. 2018;28(5):927-938. doi: 10.1080/10543406.2017.1405012. Epub 2017 Nov 29.


We investigate the survival distribution of the patients who have survived over a certain time period. This is called a conditional survival distribution. In this paper, we show that one-sample estimation, two-sample comparison and regression analysis of conditional survival distributions can be conducted using the regular methods for unconditional survival distributions that are provided by the standard statistical software, such as SAS and SPSS. We conduct extensive simulations to evaluate the finite sample property of these conditional survival analysis methods. We illustrate these methods with real clinical data.

Keywords: Delta method; Fieller method; Kaplan-Meier estimator; Log-rank test; Martingale central limit theorem; Proportional hazards model.

Publication types

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

MeSH terms

  • Data Interpretation, Statistical*
  • Humans
  • Models, Statistical*
  • Proportional Hazards Models*
  • Survival Analysis