This article, “Effective Sample Size for the Kaplan–Meier Estimator: A Valuable Measure of Uncertainty?”, is authored by Toby Hackmann, Doranne Thomassen, Anne M. Stiggelbout, Saskia le Cessie, Hein Putter, Liesbeth C. de Wreede, Ewout W. Steyerberg, with contributions from the 4D PICTURE Consortium (2025).
It examines the concept of effective sample size for the Kaplan–Meier estimator and its value as a measure of uncertainty in survival analysis. The authors explore how the effective sample size changes over time and how it reflects the decreasing amount of information available due to censoring (incomplete follow-up). Their findings clarify how uncertainty in survival estimates at specific time points can be better interpreted beyond simply reporting the number of patients that remain at risk.
