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引用次数: 0
摘要
我们提出了一种非参数方法，当事件发生时间和普查时间相互独立时，可降低卡普兰-梅耶（KM）估计器的高估率。我们根据事件发生时间和剔除时间的相互关系来调整 KM 估计器。
Interval-specific censoring set adjusted Kaplan–Meier estimator
We propose a non-parametric approach to reduce the overestimation of the Kaplan-Meier (KM) estimator when the event and censoring times are independent. We adjust the KM estimator based on the inte...
期刊介绍：
Journal of Applied Statistics provides a forum for communication between both applied statisticians and users of applied statistical techniques across a wide range of disciplines. These areas include business, computing, economics, ecology, education, management, medicine, operational research and sociology, but papers from other areas are also considered. The editorial policy is to publish rigorous but clear and accessible papers on applied techniques. Purely theoretical papers are avoided but those on theoretical developments which clearly demonstrate significant applied potential are welcomed. Each paper is submitted to at least two independent referees.
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