Causal Mediation Analysis with Multiple Mediators: A Simulation Approach

TL;DR

This paper presents a comprehensive simulation-based approach for causal mediation analysis involving multiple mediators, accommodating complex models with parametric and nonparametric methods, including deep neural networks.

Contribution

It introduces a unified framework for estimating various mediation effects using simulation, with both parametric and neural network-based nonparametric implementations.

Findings

Effective estimation of mediation effects demonstrated on real datasets

Parametric models require correct specification for accurate results

Nonparametric neural network models reduce reliance on strict assumptions

Abstract

Analyses of causal mediation often involve exposure-induced confounders or, relatedly, multiple mediators. In such applications, researchers aim to estimate a variety of different quantities, including interventional direct and indirect effects, multivariate natural direct and indirect effects, and/or path-specific effects. This study introduces a general approach to estimating all these quantities by simulating potential outcomes from a series of distribution models for each mediator and the outcome. Building on similar methods developed for analyses with only a single mediator (Imai et al. 2010), we first outline how to implement this approach with parametric models. The parametric implementation can accommodate linear and nonlinear relationships, both continuous and discrete mediators, and many different types of outcomes. However, it depends on correct specification of each model used to simulate the potential outcomes. To address the risk of misspecification, we also introduce an alternative implementation using a novel class of nonparametric models, which leverage deep neural networks to approximate the relevant distributions without relying on strict assumptions about functional form. We illustrate both methods by reanalyzing the effects of media framing on attitudes toward immigration (Brader et al. 2008) and the effects of prenatal care on preterm birth (VanderWeele et al. 2014).