Sharp nonparametric bounds for decomposition effects with two binary mediators

12/27/2021
by   Erin E Gabriel, et al.
0

In randomized trials, once the total effect of the intervention has been estimated, it is often of interest to explore mechanistic effects through mediators along the causal pathway between the randomized treatment and the outcome. In the setting with two sequential mediators, there are a variety of decompositions of the total risk difference into mediation effects. We derive sharp and valid bounds for a number of mediation effects in the setting of two sequential mediators both with unmeasured confounding with the outcome. We provide five such bounds in the main text corresponding to two different decompositions of the total effect, as well as the controlled direct effect, with an additional thirty novel bounds provided in the supplementary materials corresponding to the terms of twenty-four four-way decompositions. We also show that, although it may seem that one can produce sharp bounds by adding or subtracting the limits of the sharp bounds for terms in a decomposition, this almost always produces valid, but not sharp bounds that can even be completely noninformative. We investigate the properties of the bounds by simulating random probability distributions under our causal model and illustrate how they are interpreted in a real data example.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/11/2020

Nonparametric bounds for causal effects in imperfect randomized experiments

Nonignorable missingness and noncompliance can occur even in well-design...
research
02/24/2020

Causal bounds for outcome-dependent sampling in observational studies

Outcome-dependent sampling designs are common in many different scientif...
research
07/19/2019

Interventional Effect Models for Multiple Mediators

In settings that involve multiple mediators, approaches focusing on fine...
research
07/30/2020

Decomposition of the Total Effect for Two Mediators: A Natural Counterfactual Interaction Effect Framework

Mediation analysis has been used in many disciplines to explain the mech...
research
12/21/2021

Doubly-Valid/Doubly-Sharp Sensitivity Analysis for Causal Inference with Unmeasured Confounding

We study the problem of constructing bounds on the average treatment eff...
research
05/20/2022

What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment

The fundamental problem of causal inference – that we never observe coun...
research
08/27/2020

Pleiotropy robust methods for multivariable Mendelian randomization

Mendelian randomization is a powerful tool for inferring the presence, o...

Please sign up or login with your details

Forgot password? Click here to reset