Nearly all scientific studies explore causality, which will be met by directed acyclic graphs (DAGs). This paper systematically introduces graphic language, basic and interference rules of DAGs, and their applications into identifying research questions, understanding and undertaking research designs, guiding data analysis, classifying biases, etc. DAGs play key roles in causality studies.
几乎所有的科学研究都在探索因果关系，有向无环图（DAGs）是因果关系研究的图形工具。本文系统地介绍了DAGs的图形语言、基本规则和干扰规则，及其在识别研究问题、理解和实施研究设计、指导数据分析、偏倚分类等方面的应用。DAGs对因果关系的研究具有重要的指导价值。.
Keywords: Bias; Causality; Directed acyclic graphs; Research designs.