因果推理
推论
趋同(经济学)
数据科学
领域(数学)
计算机科学
集合(抽象数据类型)
因果关系(物理学)
认知科学
认识论
人工智能
心理学
计量经济学
数学
哲学
经济
物理
程序设计语言
纯数学
量子力学
经济增长
作者
Jean‐Baptiste Pingault,Rebecca C Richmond,George Davey Smith
出处
期刊:Cold Spring Harbor Perspectives in Medicine
[Cold Spring Harbor Laboratory]
日期:2021-09-27
卷期号:12 (3): a041271-a041271
被引量:8
标识
DOI:10.1101/cshperspect.a041271
摘要
The set of methods discussed in this collection has emerged from the convergence of two scientific fields-genetics and causal inference. In this introduction, we discuss relevant aspects of each field and show how their convergence arises from the natural experiments that genetics offer. We present introductory concepts useful to readers unfamiliar with genetically informed methods for causal inference. We conclude that existing applications and foreseeable developments should ensure that we rapidly reap the rewards of this relatively new field, not only in terms of our understanding of human disease and development, but also in terms of tangible translational applications.
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