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[Directed acyclic graphs: languages, rules and applications].

摘要:

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, <i>etc</i>. DAGs play key roles in causality studies.

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作者: Y J,Zheng [1] ; N Q,Zhao [2]
作者单位: Department of Public Health Microbiology, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China; Key Laboratory of Health Technology Assessment, Ministry of Health, Fudan University, Shanghai 200032, China. [1] Department of Biostatistics, School of Public Health, Fudan University, Shanghai 200032, China. [2]
期刊:
《Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi》 2017年38卷8期1140-1144页
DOI: 10.3760/cma.j.issn.0254-6450.2017.08.029
发布时间: 2019-04-03
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