# Transporting stochastic direct and indirect effects to new populations

## TL;DR

This paper introduces new estimators for transported stochastic direct and indirect effects to understand intervention differences across populations, addressing a gap in existing methods.

## Contribution

The paper proposes novel estimators for transported mediation effects, including stabilized weighted, doubly robust, and targeted minimum loss-based estimators.

## Key findings

- The estimators perform well in finite samples in simulations.
- The doubly robust estimators provide consistent estimates under model misspecification.
- The methods enable analysis of intervention effects in new populations.

## Abstract

Transported mediation effects may contribute to understanding how and why interventions may work differently when applied to new populations. However, we are not aware of any estimators for such effects. Thus, we propose several different estimators of transported stochastic direct and indirect effects: an inverse-probability of treatment stabilized weighted estimator, a doubly robust estimator that solves the estimating equation, and a doubly robust substitution estimator in the targeted minimum loss-based framework. We demonstrate their finite sample properties in a simulation study.