Variance Inflation Due to Censoring in Survival Probability Estimates


  • Szilard Nemes AstraZeneca
  • Andreas Gustavsson AstraZeneca
  • Ziad Taib Atlasbiostat



Survival, Right-censoring, Standard error, Kaplan-Meier


One of the most obvious features of time-to-event data is the occurrence of censoring. Rarely, if ever, studies are conducted until all participants experience the event of interest. Some participants survive beyond the end of follow-up time, some drop out from the studies for various non-study related reasons. During research planning it is paramount to consider the effect of censoring the follow-up times on the estimates. Herein, we look into the possibility of assessing
the loss of information, as measured by the variability of the survival probability estimates under right censoring. We provide the researchers with an easy to use formula to assess the magnitude of variance inflation due to censoring. Additionally, we conducted simulation studies assuming various survival distributions. We conclude that the provided variance inflation estimator can be an accurate practical tool for applied statisticians.


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How to Cite

Nemes, S., Gustavsson, A., & Taib, Z. (2020). Variance Inflation Due to Censoring in Survival Probability Estimates. Statistica, 80(4), 395–412.