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Asymptotic results for fitting marginal hazards models from stratified case-cohort studies with multiple disease outcomes.
Journal of the Korean Statistical Society ( IF 0.6 ) Pub Date : 2010-04-24 , DOI: 10.1016/j.jkss.2010.03.005
Sangwook Kang 1 , Jianwen Cai
Affiliation  

In stratified case-cohort designs, samplings of case-cohort samples are conducted via a stratified random sampling based on covariate information available on the entire cohort members. In this paper, we extended the work of Kang and Cai (2009) to a generalized stratified case-cohort study design for failure time data with multiple disease outcomes. Under this study design, we developed weighted estimating procedures for model parameters in marginal multiplicative intensity models and for the cumulative baseline hazard function. The asymptotic properties of the estimators are studied using martingales, modern empirical process theory, and results for finite population sampling.

中文翻译:

来自具有多种疾病结果的分层病例队列研究拟合边际风险模型的渐近结果。

在分层病例队列设计中,病例队列样本的抽样是通过分层随机抽样根据整个队列成员的可用协变量信息进行的。在本文中,我们将 Kang 和 Cai (2009) 的工作扩展到具有多种疾病结果的失败时间数据的广义分层病例队列研究设计。在本研究设计下,我们为边际乘法强度模型中的模型参数和累积基线危险函数开发了加权估计程序。使用鞅、现代经验过程理论和有限总体抽样的结果来研究估计量的渐近特性。
更新日期:2010-04-24
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