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Clustered Survival Data with Left-truncation

机译:具有左截断的聚类生存数据

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Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry. Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties are investigated via simulation studies, and the suggested estimators are used in a study of prostate cancer based on the Finnish twin cohort where a twin pair is included only if both twins were alive in 1974.
机译:在生存研究中,经常发生左截短现象,并且众所周知如何在单变量生存时间中进行处理。然而,关于如何估计具有延迟输入的聚类生存数据的半参数模型中的依赖参数和回归效应的结果很少。令人惊讶的是,现有方法仅处理特殊情况。在本文中,我们阐明了不同的左截断形式,并为特定截断方案下的半参数生存模型建议了估计量。建立估计量的大样本属性。通过模拟研究来研究小样本属性,并根据芬兰双胞胎队列在前列腺癌研究中使用建议的估计量,其中只有当双胞胎在1974年都活着时才包括一对双胞胎。

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