The central role of the mediator process in mediation analysis

Music City Center 

Causal mediation has traditionally been framed as the effect of an exposure on an outcome through some intermediate variable, where each variable is measured at three sequential time points. However, definitions of mediated effects and their corresponding identification assumptions generally ignore the fact that the mediator of interest is, in many if not most circumstances, a stochastic process indexed by time from baseline to follow-up. I demonstrate that the failure to account for the mediator process has important implications for defining the relevant causal estimand of interest as well as its identification and estimation. Additionally, I discuss versions of direct and indirect effect definitions that account for the entire mediator process and how they relate to corresponding versions that do not.

Causal inference

Functional data analysis

Mediation

Stochastic process