Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.
Biostatistics. 2012 Jan;13(1):89-100. doi: 10.1093/biostatistics/kxr021. Epub 2011 Aug 19.
Nested case-control (NCC) design is used frequently in epidemiological studies as a cost-effective subcohort sampling strategy to conduct biomarker research. Sampling strategy, on the other hoand, creates challenges for data analysis because of outcome-dependent missingness in biomarker measurements. In this paper, we propose inverse probability weighted (IPW) methods for making inference about the prognostic accuracy of a novel biomarker for predicting future events with data from NCC studies. The consistency and asymptotic normality of these estimators are derived using the empirical process theory and convergence theorems for sequences of weakly dependent random variables. Simulation and analysis using Framingham Offspring Study data suggest that the proposed methods perform well in finite samples.
巢式病例对照(NCC)设计常被用于流行病学研究中,作为一种经济有效的亚组抽样策略,以开展生物标志物研究。然而,抽样策略给数据分析带来了挑战,因为生物标志物测量的缺失是依赖于结果的。在本文中,我们提出了逆概率加权(IPW)方法,用于使用来自 NCC 研究的数据,对预测未来事件的新型生物标志物的预后准确性进行推断。这些估计量的一致性和渐近正态性是使用经验过程理论和弱相依随机变量序列的收敛定理推导出来的。使用弗雷明汉后代研究数据的模拟和分析表明,所提出的方法在有限样本中表现良好。