Dealing with effect decomposition and intermediate confounding in causal mediation analysis

Mediation analysis concerns decomposition of a causal effect into direct and mediated effects. The simplicity of current methods does not match the complexity of realistic data: estimation principles for continuous data are being applied to other data types with no justification; moreover, the problem of confounding is largely ignored. This project aims to overcome these limitations.