4 The Kaplan–Meier Estimator
Parametric models need a family of distributions to be assumed. The Kaplan–Meier estimator (1958) estimates the survival function with no such assumption, using only the order in which events and censorings occur. It is the most widely used method in survival analysis: almost every clinical paper with a time-to-event outcome shows Kaplan–Meier curves. This section derives the estimator, computes its standard error and confidence intervals, and shows how to read survival curves and their medians.
4.1 The product-limit estimator
4.2 Greenwood’s formula and confidence intervals
4.3 The median and reading the curve
4.4 Kaplan–Meier estimation in software
4.5 Practice Problems
4.2 Greenwood’s formula and confidence intervals
4.3 The median and reading the curve
4.4 Kaplan–Meier estimation in software
4.5 Practice Problems
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