Causality, Mediation and Time: A Dynamic Viewpoint
本文指出因果建模常忽略时间动态，提出基于局部独立图和动态路径分析的机制性因果理解，并以瑞士HIV队列数据为例展示方法，适合关注因果推断方法的研究者。
Time dynamics are often ignored in causal modelling. Clearly, causality must operate in time and we show how this corresponds to a mechanistic, or system, understanding of causality. The established counterfactual definitions of direct and indirect effects depend on an ability to manipulate the mediator which may not hold in practice, and we argue that a mechanistic view may be better. Graphical representations based on local independence graphs and dynamic path analysis are used to facilitate communication as well as providing an overview of the dynamic relations 'at a glance'. The relationship between causality as understood in a mechanistic and in an interventionist sense is discussed. An example using data from the Swiss HIV Cohort Study is presented.