Graber-Naidich Anna, Gorfine Malka, Malone Kathleen E, Hsu Li
Faculty of Industrial Engineering and Management, Technion City, Haifa 32000, Israel.
Lifetime Data Anal. 2011 Apr;17(2):175-94. doi: 10.1007/s10985-010-9178-5. Epub 2010 Dec 12.
Case-control family data are now widely used to examine the role of gene-environment interactions in the etiology of complex diseases. In these types of studies, exposure levels are obtained retrospectively and, frequently, information on most risk factors of interest is available on the probands but not on their relatives. In this work we consider correlated failure time data arising from population-based case-control family studies with missing genotypes of relatives. We present a new method for estimating the age-dependent marginalized hazard function. The proposed technique has two major advantages: (1) it is based on the pseudo full likelihood function rather than a pseudo composite likelihood function, which usually suffers from substantial efficiency loss; (2) the cumulative baseline hazard function is estimated using a two-stage estimator instead of an iterative process. We assess the performance of the proposed methodology with simulation studies, and illustrate its utility on a real data example.
病例对照家系数据目前被广泛用于研究基因 - 环境相互作用在复杂疾病病因学中的作用。在这类研究中，暴露水平是通过回顾性获取的，而且通常情况下，关于大多数感兴趣的风险因素的信息可从先证者处获得，但无法从其亲属处获得。在这项工作中，我们考虑了基于人群的病例对照家系研究中出现的相关失效时间数据，其中亲属的基因型缺失。我们提出了一种估计年龄依赖性边际风险函数的新方法。所提出的技术有两个主要优点：（1）它基于伪完全似然函数而非伪复合似然函数，后者通常会遭受相当大的效率损失；（2）累积基线风险函数是使用两阶段估计器而非迭代过程来估计的。我们通过模拟研究评估了所提出方法的性能，并在一个实际数据示例中说明了其效用。
