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Fully nonparametric estimation of the marginal survival function based on case-control clustered data

机译:基于案例控制聚类数据的边际生存函数的完全非参数估计

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A case-control family study is a study where individuals with a disease of interest (case probands) and individuals without the disease (control probands) are randomly sampled from a well-defined population. Possibly right-censored age at onset and disease status are observed for both probands and their relatives. Correlation among the outcomes within a family is induced by factors such as inherited genetic susceptibility, shared environment, and common behavior patterns. For this setting, we present a nonparametric estimator of the marginal survival function, based on local linear estimation of conditional survival functions. Asymptotic theory for the estimator is provided, making this paper the first to present for this data setting a fully nonparametric estimator with proven consistency. Simulation results are presented showing that the method performs well. The method is illustrated on data from a prostate cancer study.
机译:病例对照家庭研究是从定义明确的人群中随机抽取有目标疾病的个体(先证者)和没有疾病的个体(先证者)的研究。对于先证者及其亲属,可能在发病和疾病状况方面都进行了右删节。家庭遗传结果之间的相关性是由遗传遗传易感性,共享环境和共同行为模式等因素引起的。对于此设置,我们基于条件生存函数的局部线性估计,提供了边际生存函数的非参数估计量。提供了估计器的渐近理论,这使本文成为第一个针对此数据提出具有完全一致性的完全非参数估计器的论文。仿真结果表明该方法性能良好。前列腺癌研究的数据说明了该方法。

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