A modification of Peto's nonparametric estimation of survival curves for interval-censored data
A modification of Peto's nonparametric estimation of survival curves for interval-censored data
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DOI：
10.1111/j.0006-341x.2002.00439.x
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发表时间：
2002-06-01
期刊：
影响因子：
1.9
通讯作者：
Ng, MP
中科院分区：
文献类型：
--
作者：
Ng, MP
Peto（1973，Applied Statistics，22，86-91）给出了区间删失数据生存函数的非参数广义极大似然估计。他的方法倾向于将概率质量集中在区间的端点，即使是普通的分组数据，而不是将它们分散在区间中，因为人们可能会期望它们在潜在的分布中。我们描述了一种克服这一点的修改。当应用于分组数据时，新的估计减少到标准的二项式估计。当应用于仅由精确或右删失观察值组成的生存数据时，它也减少到Kaplan-Meier估计。这两种估计都是最大似然估计，但都基于对。区间的端点。
Peto (1973, Applied Statistics, 22, 86-91) gave a nonparametric generalized maximum-likelihood estimate of the survival function for interval-censored data. His method has a tendency to concentrate probability masses at the endpoints of the intervals, even for the ordinary grouped data, instead of spreading them through the intervals, as one might expect them to be in the underlying distribution. We describe a modification that overcomes this. The new estimate reduces to the standard binomial estimate when applied to grouped data. It also reduces to the Kaplan-Meier estimate when applied to survival data that consist of only exact or right-censored observations. Both estimates are maximum-likelihood estimates but are based on different interpretations of the. endpoints of the intervals.