This article provides an overview of recent developments in mediation analysis, that is,
analyses used to assess the relative magnitude of different pathways and mechanisms by …

This review presents empirical researchers with recent advances in causal inference, and
stresses the paradigmatic shifts that must be undertaken in moving from traditional statistical …

Path models to test claims about mediation and moderation are a staple of psychology. But
applied researchers may sometimes not understand the underlying causal inference …

Recent advances in the causal inference literature on mediation have extended traditional
approaches to direct and indirect effects to settings that allow for interactions and non …

This book builds on and is a sequel to our book Targeted Learning: Causal Inference for
Observational and Experimental Studies (2011). Since the publication of this first book on …

The overall effect of an exposure on an outcome, in the presence of a mediator with which
the exposure may interact, can be decomposed into 4 components:(1) the effect of the …

This paper investigates the problem of bounding counterfactual queries from an arbitrary
collection of observational and experimental distributions and qualitative knowledge about …

Decision-making systems based on AI and machine learning have been used throughout a
wide range of real-world scenarios, including healthcare, law enforcement, education, and …

Traditionally in the social sciences, causal mediation analysis has been formulated,
understood, and implemented within the framework of linear structural equation models. We …

Causal mediation analysis is routinely conducted by applied researchers in a variety of
disciplines. The goal of such an analysis is to investigate alternative causal mechanisms by …