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Semiparametric random censorship models for survival data with long-term survivors

机译:具有长期幸存者的生存数据的Semiparametric随机审查模型

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In this article, we study a semiparametric random censorship model for survival data in the presence of long-term survivors. Local likelihood method is employed to estimate the conditional mean regression function of binary random variables. The proposed estimators for the survival function and the cure rate, as well as their asymptotic properties, are investigated based on empirical and U-statistical processes. In particular, the proposed estimator for the cure rate is shown to be superior over the previous estimator considered by Maller and Zhou in the sense of having a smaller asymptotic variance. This semiparametric random censorship model with related estimation methods provide an efficient alternative for survival analysis with long-term survivors.
机译:在本文中,我们研究了在存在长期幸存者存在下的生存数据的半射目随机审查模型。本地似然方法用于估计二进制随机变量的条件平均回归函数。基于实证和U形统计程序,研究了生存函数和治愈率和治愈率的估计和治愈率,以及它们的渐近性。特别是,对于治愈率的建议估算者被证明是在具有较小渐近方差的比较较小的渐近差异的先前估计器中优越。具有相关估计方法的该半脉印随机审查模型提供了具有长期幸存者的生存分析的有效替代方案。

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