NON-HIERARCHICAL LOGISTIC-MODELS AND CASE-ONLY DESIGNS FOR ASSESSING SUSCEPTIBILITY IN POPULATION-BASED CASE-CONTROL STUDIES
NON-HIERARCHICAL LOGISTIC-MODELS AND CASE-ONLY DESIGNS FOR ASSESSING SUSCEPTIBILITY IN POPULATION-BASED CASE-CONTROL STUDIES
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DOI：
10.1002/sim.4780130206
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发表时间：
1994-01-30
影响因子：
2
通讯作者：
TAYLOR, JA
中科院分区：
文献类型：
--
作者：
PIEGORSCH, WW;WEINBERG, CR;TAYLOR, JA
本文介绍了如何在病例对照研究中评估疾病易感性的遗传成分，在病例对照研究中，病例和对照组独立于人群进行抽样。与家族聚集和连锁研究相反，受试者被假定为无关。逻辑模型可用于测试表型或基因型的可解释性，并估计环境和遗传因素之间的相互作用。这样的交互提供了一个非层次模型在生物学上有意义的背景的例子。此外，如果暴露和遗传类别独立发生，并且疾病罕见，则仅基于病例的分析是有效的，并且比基于完整数据的分析提供更好的精度来估计基因环境相互作用。
This article describes how genetic components of disease susceptibility can be evaluated in case-control studies, where cases and controls are sampled independently from the population at large. Subjects are assumed unrelated, in contrast to studies of familial aggregation and linkage. The logistic model can be used to test collapsibility over phenotypes or genotypes, and to estimate interactions between environmental and genetic factors. Such interactions provide an example of a context where non-hierarchical models make sense biologically. Also, if the exposure and genetic categories occur independently and the disease is rare, then analyses based only on cases are valid, and offer better precision for estimating gene environment interactions than those based on the full data.