Identification of causal direct-indirect effects without untestable assumptions

09/26/2020
by   Takahiro Hoshino, et al.
0

In causal mediation analysis, identification of existing causal direct or indirect effects requires untestable assumptions in which potential outcomes and potential mediators are independent. This paper defines a new causal direct and indirect effect that does not require the untestable assumptions. We show that the proposed measure is identifiable from the observed data, even if potential outcomes and potential mediators are dependent, while the existing natural direct or indirect effects may find a pseudo-indirect effect when the untestable assumptions are violated.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset