 Variance Inflation Due to Censoring in Survival Probability EstimatesSzilard Nemes (),
Andreas Gustavsson and
Ziad Taib
Statistica, 2020, vol. 80, issue 4, 395-412 Abstract: 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. Keywords: Survival; Right-censoring; Standard error; Kaplan-Meier (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bot:rivsta:v:80:y:2020:i:4:p:395-412 Access Statistics for this article Statistica is currently edited by Department of Statistics, University of Bologna More articles in Statistica from Department of Statistics, University of Bologna Contact information at EDIRC. |
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