On estimation of linear transformation models with nested case-control sampling.

On estimation of linear transformation models with nested case-control sampling.
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关于嵌套病例对照抽样线性变换模型的估计。

DOI:
10.1007/s10985-011-9203-3
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发表时间:
2012-01
影响因子:
1.3
通讯作者:
Liu M
Liu M
中科院分区:
数学3区
文献类型:
--
作者:
Lu W;Liu M

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嵌套病例对照抽样因其成本效益被广泛应用于大规模流行病学队列研究中,但其数据分析主要依赖于Cox比例风险模型。本文考虑了一类用于分析NCC数据的线性变换模型,并提出了一种逆选择概率加权估计方程的推理方法。建立了回归系数估计的相合性和渐近正态性质。我们证明了渐近方差具有封闭的解析形式,并且很容易估计。数值研究支持了该理论,并给出了一个应用于Wilms肿瘤研究的方法。
Nested case–control (NCC) sampling is widely used in large epidemiological cohort studies for its cost effectiveness, but its data analysis primarily relies on the Cox proportional hazards model. In this paper, we consider a family of linear transformation models for analyzing NCC data and propose an inverse selection probability weighted estimating equation method for inference. Consistency and asymptotic normality of our estimators for regression coefficients are established. We show that the asymptotic variance has a closed analytic form and can be easily estimated. Numerical studies are conducted to support the theory and an application to the Wilms’ Tumor Study is also given to illustrate the methodology.
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