孟德尔随机化
观察研究
因果推理
混淆
工具变量
随机对照试验
因果关系
流行病学
因果关系(物理学)
代理(统计)
医学
计算机科学
计量经济学
生物
遗传学
机器学习
数学
病理
基因
认识论
哲学
物理
量子力学
遗传变异
基因型
作者
Debbie A. Lawlor,Roger Harbord,Jonathan A C Sterne,Nicholas J. Timpson,George Davey Smith
摘要
Observational epidemiological studies suffer from many potential biases, from confounding and from reverse causation, and this limits their ability to robustly identify causal associations. Several high-profile situations exist in which randomized controlled trials of precisely the same intervention that has been examined in observational studies have produced markedly different findings. In other observational sciences, the use of instrumental variable (IV) approaches has been one approach to strengthening causal inferences in non-experimental situations. The use of germline genetic variants that proxy for environmentally modifiable exposures as instruments for these exposures is one form of IV analysis that can be implemented within observational epidemiological studies. The method has been referred to as 'Mendelian randomization', and can be considered as analogous to randomized controlled trials. This paper outlines Mendelian randomization, draws parallels with IV methods, provides examples of implementation of the approach and discusses limitations of the approach and some methods for dealing with these.
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