Replication data for: A General Approach to Causal Mediation Analysis

We argue and demonstrate that this is problematic for three reasons; the lack of a general definition of causal mediation effects independent of a particular statistical model, the inability to specify the key identification assumption, and the difficulty of extending the framework to nonlinear models.

In this paper, we propose an alternative approach that overcomes these limitations. Our approach is general because it offers the definition, identification, estimation, and sensitivity analysis of causal mediation effects without reference to any specific statistical model. Further, our approach explicitly links these four elements closely together within a single framework.