Survival analysis

Bendix Carstensen
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Abstract

This chapter describes survival analysis. Survival analysis concerns data where the outcome is a length of time, namely the time from inclusion in the study (such as diagnosis of some disease) till death or some other event — hence the term 'time to event analysis', which is also used. There are two primary targets normally addressed in survival analysis: survival probabilities and event rates. The chapter then looks at the life table estimator of survival function and the Kaplan–Meier estimator of survival. It also considers the Cox model and its relationship with Poisson models, as well as the Fine–Gray approach to competing risks.
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生存分析
本章描述了生存分析。生存分析关注的是结果是一段时间的数据,即从纳入研究(如某些疾病的诊断)到死亡或其他事件的时间——因此也使用了术语“事件时间分析”。在生存分析中通常有两个主要目标:生存概率和事件发生率。然后,本章研究了生存函数的生命表估计量和生存的Kaplan-Meier估计量。它还考虑了Cox模型及其与泊松模型的关系,以及竞争风险的Fine-Gray方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Survival analysis Case-control and case-cohort studies Do not group quantitative variables Regression models Using R
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