ASYMPTOTIC THEORY FOR NESTED CASE-CONTROL SAMPLING IN THE COX REGRESSION-MODEL
ASYMPTOTIC THEORY FOR NESTED CASE-CONTROL SAMPLING IN THE COX REGRESSION-MODEL
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DOI：
10.1214/aos/1176348895
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发表时间：
1992-12-01
影响因子：
4.5
通讯作者：
LANGHOLZ, B
中科院分区：
文献类型：
--
作者：
GOLDSTEIN, L;LANGHOLZ, B
通过提供流行病学队列研究中巢式病例对照抽样的概率模型，可以使用Andersen和Gill的过程和鞅理论导出考克斯比例风险模型中回归参数的最大偏似然估计的相合性和渐近正态性。给出了渐近方差的一般表达式，并用于计算在某些重要的特殊情况下相对于全队列方差的渐近相对效率。
By providing a probabilistic model for nested case-control sampling in epidemiologic cohort studies, consistency and asymptotic normality of the maximum partial likelihood estimator of regression parameters in a Cox proportional hazards model can be derived using process and martingale theory as in Andersen and Gill. A general expression for the asymptotic variance is given and used to calculate asymptotic relative efficiencies relative to the full cohort variance in some important special cases.