Collider scope: when selection bias can substantially influence observed associations.
Collider scope: when selection bias can substantially influence observed associations.
复制标题
DOI：
10.1093/ije/dyx206
复制
发表时间：
2018-02-01
影响因子：
7.7
通讯作者：
Davey Smith G
中科院分区：
文献类型：
--
作者：
Munafò MR;Tilling K;Taylor AE;Evans DM;Davey Smith G
大规模的横断面和队列研究改变了我们对健康结果的遗传和环境决定因素的理解。然而，这些样本的代表性可能是有限的，无论是通过选择到研究，或从研究随着时间的推移磨损。在这里，我们探讨了这种选择偏差对从这些研究中获得的结果的潜在影响，从这个角度来看，这相当于对对撞机的条件（即一种形式的对撞机偏见）。虽然人们承认，选择偏差将有很大的影响，代表性和患病率的估计，它往往被认为不应该有很大的影响，协会的估计。我们认为，因为选择可以诱导碰撞机偏见（发生时，两个变量独立影响第三个变量，第三个变量是有条件的），选择可以导致实质上有偏见的协会估计。特别是，与表型相关的选择可能会偏向与那些表型相关的遗传变异的关联。在模拟中，我们表明，即使是适度的影响，选择或磨损，一项研究可以产生偏见和潜在的误导性估计表型和基因型的关联。我们的研究结果突出了了解您的研究样本代表哪个人群的价值。如果影响选择和损耗的因素是已知的，它们可以被调整。例如，在出生队列研究中，获得大多数参与者的DNA，可以调查多基因评分预测随后参与的程度，这反过来又可以对偏倚可能扭曲估计的程度进行敏感性分析。
Large-scale cross-sectional and cohort studies have transformed our understanding of the genetic and environmental determinants of health outcomes. However, the representativeness of these samples may be limited–either through selection into studies, or by attrition from studies over time. Here we explore the potential impact of this selection bias on results obtained from these studies, from the perspective that this amounts to conditioning on a collider (i.e. a form of collider bias). Whereas it is acknowledged that selection bias will have a strong effect on representativeness and prevalence estimates, it is often assumed that it should not have a strong impact on estimates of associations. We argue that because selection can induce collider bias (which occurs when two variables independently influence a third variable, and that third variable is conditioned upon), selection can lead to substantially biased estimates of associations. In particular, selection related to phenotypes can bias associations with genetic variants associated with those phenotypes. In simulations, we show that even modest influences on selection into, or attrition from, a study can generate biased and potentially misleading estimates of both phenotypic and genotypic associations. Our results highlight the value of knowing which population your study sample is representative of. If the factors influencing selection and attrition are known, they can be adjusted for. For example, having DNA available on most participants in a birth cohort study offers the possibility of investigating the extent to which polygenic scores predict subsequent participation, which in turn would enable sensitivity analyses of the extent to which bias might distort estimates.
登录
查看更多内容
影响因子：
5.8
作者：
Lee, S. H.;Yang, J.;Wray, N. R.
通讯作者：
Wray, N. R.
影响因子：
3.5
作者：
Evans, David M.;Visscher, Peter M.;Wray, Naomi R.
通讯作者：
Wray, Naomi R.
影响因子：
10.5
作者：
Elwert F;Winship C
通讯作者：
Winship C
影响因子：
30.8
作者：
Bulik-Sullivan B;Finucane HK;Anttila V;Gusev A;Day FR;Loh PR;ReproGen Consortium;Psychiatric Genomics Consortium;Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3;Duncan L;Perry JR;Patterson N;Robinson EB;Daly MJ;Price AL;Neale BM
通讯作者：
Neale BM
影响因子：
5.4
作者：
Hernán, MA;Hernández-Díaz, S;Robins, JM
通讯作者：
Robins, JM