Wang T L, Mou Y T, Kan H, Li Y X, Fan W, Dai J H, Zheng Y J
Department of Epidemiology, Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.
Department of Epidemiology and Biostatistics, School of Public Health, Xinjiang Medical University, Urumqi 830011, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2020 May 10;41(5):782-787. doi: 10.3760/cma.j.cn112338-20190929-00711.
In causal inference, the concept of temporality (or directionality) has not been fully clarified. Starting from causal thinking, this paper divides the time axis in nature into three time domains and two time points by the occurrence timings of both a real cause and a real effect. This has anchored that causal inference can only be realized in the third domain. The measured temporalities can be divided into five types: cross-first-to-third-domain longitudinal (or experimental temporalities), cross-second-to-third-domain longitudinal, within-domain longitudinal, within-domain reversely longitudinal, and within-domain transversal (or observational temporalities). This new classification encompasses all measurement strategies, either for first or multiple measurements, or timely and delayed measurements. Except that the actual measurement for the cause occurs either before its occurrence (only in experiment) or within the second domain, all other measurements are similar to the act of historical reconstruction or "archaeology" , where the importance of measured temporalities may be inferior to the accuracy of the measurements. From the point of view that research design should integrate bias design, this new classification for measured temporalities based on the time axis in Nature, which has a clear meaning and helps to judge the possible biases in the observation methods, provides a basis for correct causal inferences.
在因果推断中，时间性（或方向性）的概念尚未得到充分阐明。本文从因果思维出发，根据真实原因和真实结果的发生时机，将自然界中的时间轴划分为三个时域和两个时间点。这确定了因果推断只能在第三个时域中实现。所测量的时间性可分为五种类型：跨第一到第三域纵向（或实验性时间性）、跨第二到第三域纵向、域内纵向、域内反向纵向和域内横向（或观察性时间性）。这种新的分类涵盖了所有测量策略，无论是单次测量还是多次测量，以及即时测量和延迟测量。除了对原因的实际测量发生在其出现之前（仅在实验中）或在第二个域内，所有其他测量都类似于历史重建或“考古”行为，其中所测量时间性的重要性可能不如测量的准确性。从研究设计应整合偏差设计的角度来看，这种基于自然界时间轴对所测量时间性的新分类具有明确的意义，有助于判断观察方法中可能存在的偏差，为正确的因果推断提供了依据。
