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Causality, mediation and time: a dynamic viewpoint
Article first published online: 7 MAR 2012
© 2012 Royal Statistical Society
Journal of the Royal Statistical Society: Series A (Statistics in Society)
Volume 175, Issue 4, pages 831–861, October 2012
How to Cite
Aalen, O. O., Røysland, K., Gran, J. M. and Ledergerber, B. (2012), Causality, mediation and time: a dynamic viewpoint. Journal of the Royal Statistical Society: Series A (Statistics in Society), 175: 831–861. doi: 10.1111/j.1467-985X.2011.01030.x
- Issue published online: 3 OCT 2012
- Article first published online: 7 MAR 2012
- [Received March 2010. Final revision October 2011]
- Causal inference;
- Dynamic path analysis;
- Granger causality;
- Local independence;
Summary. 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.