Survivor function estimators under group sequential monitoring based on the logrank statistic

Malka Gorfine

Research output: Contribution to journalArticlepeer-review


In this paper we investigate a group sequential analysis of censored survival data with staggered entry, in which the trial is monitored using the logrank test while comparisons of treatment and control Kaplan-Meier curves at various time points are performed at the end of the trial. We concentrate on two-sample tests under local alternatives. We describe the relationship of the asymptotic bias of Kaplan-Meier curves between the two groups. We show that even if the asymptotic bias of the Kaplan-Meier curve is negligible relative to the true survival, this is not the case for the difference between the curves of the two arms of the trial. A corrected estimator for the difference between the survival curves is presented and by simulations we show that the corrected estimator reduced the bias dramatically and has a smaller variance. The methods of estimation are applied to the Beta-Blocker Heart Attack Trial (1982), a well-known group sequential trial.

Original languageEnglish
Pages (from-to)175-193
Number of pages19
JournalLifetime Data Analysis
Issue number2
StatePublished - Jun 2003


  • Group sequential test
  • Kaplan-Meier curve
  • Local alternatives
  • Logrank test
  • Secondary parameter


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