| 李意杰,曹焱敏,范伟,张淼,刘丽丽,郑英杰.测量偏倚的方向性：基于有向无环图的结构解析[J].Chinese journal of Epidemiology,2023,44(4):643-649 |
| 测量偏倚的方向性：基于有向无环图的结构解析 |
| The directionality of measurement bias: a directed acyclic graph-based structural perspective |
| Received:September 06, 2022 |
| DOI：10.3760/cma.j.cn112338-20220906-00765 |
| KeyWord: 测量偏倚 错分偏倚 流行病学方法 有向无环图 效应估计 |
| English Key Word: Measurement bias Misclassification bias Epidemiological methods Directed acyclic graphs Effect estimate |
| FundProject:国家自然科学基金（82173582，81773490）；国家重点研发计划（2021YFC2701800，2021YFC2701801） |
| Author Name | Affiliation | E-mail | | Li Yijie | Department of Epidemiology, Key Laboratory of Public Health Safety of Ministry of Education, Key Laboratory for Health Technology Assessment, National Commission of Health, School of Public Health, Fudan University, Shanghai 200032, China
Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350108, China | | | Cao Yanmin | Department of Epidemiology, Key Laboratory of Public Health Safety of Ministry of Education, Key Laboratory for Health Technology Assessment, National Commission of Health, School of Public Health, Fudan University, Shanghai 200032, China | | | Fan Wei | Department of Epidemiology, Key Laboratory of Public Health Safety of Ministry of Education, Key Laboratory for Health Technology Assessment, National Commission of Health, School of Public Health, Fudan University, Shanghai 200032, China | | | Zhang Miao | Department of Epidemiology, Key Laboratory of Public Health Safety of Ministry of Education, Key Laboratory for Health Technology Assessment, National Commission of Health, School of Public Health, Fudan University, Shanghai 200032, China | | | Liu Lili | Department of Epidemiology, Key Laboratory of Public Health Safety of Ministry of Education, Key Laboratory for Health Technology Assessment, National Commission of Health, School of Public Health, Fudan University, Shanghai 200032, China | | | Zheng Yingjie | Department of Epidemiology, Key Laboratory of Public Health Safety of Ministry of Education, Key Laboratory for Health Technology Assessment, National Commission of Health, School of Public Health, Fudan University, Shanghai 200032, China | zhengshmu@gmail.com |
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| Abstract: |
| 测量偏倚（MB）的因果结构已有阐述但仍不完全明确；实践上，暴露与结局间效应的替代估计值（SE）的正确性是因果推断的前提，通常基于测量的暴露与测量的结局间双向无差别的错分。本文提出了基于有向无环图（DAG）的单个变量测量的结构，其MB来源于对不完美的、类似“输入/输出设备”的测量系统的选择。SE的MB受到测量系统本身和测量系统外因素的双重影响：虽然测量系统的独立性或依赖性机制仍可确保SE的MB表现为双向无差别的错分，然而测量系统外因素对SE的MB则可表现为双向无差别、单向或双向有差别的错分。此外，反向因果关系是定义在测量水平上，测量的暴露可以影响测量的结局，反之亦然。结合时序关系，DAGs有助于阐明MB的结构、机制和方向性。 |
| English Abstract: |
| Measurement bias (MB) has been described in causal structures but is still not entirely clear. In practice, the correctness of substitution estimate (SE) of effect is a prerequisite for causal inference, usually based on a bidirectionally non-differential misclassification between the measured exposure and the measured outcome. Based on a directed acyclic graph (DAG), this paper proposes a structure for the single-variable measure, where its MB is derived from the choice of an imperfect, "input/output device-like" measurement system. The MB of the SE is influenced both by the measurement system itself and by factors outside the measurement system: while the independence or dependence mechanism of the measurement system still ensures that the MB of the SE is bidirectionally non-differential; however, the misclassification can be bidirectionally non-differential, unidirectionally differential, or bidirectionally differential resulted from the factors outside the measurement system. In addition, reverse causality should be defined at the level of measurement, where measured exposures can influence measured outcomes and vice versa. Combined with temporal relationships, DAGs help elucidate MB's structures, mechanisms, and directionality. |
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