Cox regression model with time-varying coefficients in nested case-control studies.
Cox regression model with time-varying coefficients in nested case-control studies.
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DOI：
10.1093/biostatistics/kxq037
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发表时间：
2010-10
期刊：
影响因子：
2.1
通讯作者：
Mengling Liu;Wenbin Lu;R. Shore;A. Zeleniuch‐Jacquotte
中科院分区：
文献类型：
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作者：
Mengling Liu;Wenbin Lu;R. Shore;A. Zeleniuch‐Jacquotte
The nested case-control (NCC) design is a cost-effective sampling method to study the relationship between a disease and its risk factors in epidemiologic studies. NCC data are commonly analyzed using Thomas' partial likelihood approach under Cox's proportional hazards model with constant covariate effects. Here, we are interested in studying the potential time-varying effects of covariates in NCC studies and propose an estimation approach based on a kernel-weighted Thomas' partial likelihood. We establish asymptotic properties of the proposed estimator, propose a numerical approach to construct simultaneous confidence bands for time-varying coefficients, and develop a hypothesis testing procedure to detect time-varying coefficients. The proposed inference procedure is evaluated in simulations and applied to an NCC study of breast cancer in the New York University Women's Health Study.
