Non-parametric estimation of the survival function using observed failure time data depends on the underlying data generating mechanism, including the ways in which the data may be censored and/or truncated. For data arising from a single source or collected from a single cohort, a wide range of estimators have been proposed and compared in the literature. Often, however, it may be possible, and indeed advantageous, to combine and then analyse survival data that have been collected under different study designs. We review non-parametric survival analysis for data obtained by combining the most common types of cohort. We have two main goals: (i) to clarify the differences in the model assumptions and (ii) to provide a single lens through which some of the proposed estimators may be viewed. Our discussion is relevant to the meta-analysis of survival data obtained from different types of study, and to the modern era of electronic health records.

中文翻译：

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组合队列数据的生存建模：打开元生存分析和使用电子健康记录的生存分析之门


使用观察到的故障时间数据对生存函数的非参数估计取决于底层数据生成机制，包括数据可能被审查和/或截断的方式。对于来自单一来源或从单一队列收集的数据，文献中已经提出并比较了多种估计量。然而，通常情况下，组合并分析在不同研究设计下收集的生存数据可能是可能的，而且确实是有利的。我们回顾了通过组合最常见的队列类型获得的数据的非参数生存分析。我们有两个主要目标：（i）澄清模型假设的差异，（ii）提供一个单一的视角，通过它可以查看一些建议的估计量。我们的讨论与从不同类型的研究中获得的生存数据的荟萃分析以及电子健康记录的现代时代相关。