本文于2026-03-28更新。 如发现问题或者有建议，欢迎提交 Issue
相关笔记可见 github
The Kaplan-Meier estimator, independently described by Edward Kaplan and Paul Meier and conjointly published in 1958 in the Journal of the American Statistical Association, is a non-parametric statistic that allows us to estimate the survival function. [@Schuette2018]
Remember that a non-parametric statistic is not based on the assumption of an underlying probability distribution, which makes sense since survival data has a skewed distribution. [@Schuette2018]
Kaplan-Meier 估计是非参数的，因此主要用户描述性统计，主要见 github
@Schuette2018 给出了相关教程但是我觉得github对初学者更友好，直观地展现了生存模型。
- 可练习的数据来自 @Edmonson1979Different
，R中可以直接调用
survival::ovarian。
这个模型类似于互联网运营的漏斗模型和转化率相关的模型。
$$\begin{alignat}{2} S(t)&=p_{1} \cdot \dots \cdot p_{t}\\ &=\prod_{i=1}^t p_i\\ \end{alignat}$$
- S(t)衡量在t时刻，总样本存活率、转化率。
- p(t)衡量在t时刻，总样本在该时刻的存活率、转化率。
且满足关系
S(t) = S(t−1) ⋅ pt