Mediation analysis investigates the mechanisms that underlie an observed relation between
an exposure variable and an outcome variable and examines the role of an intermediate …

Background Mediation analysis methodology underwent many advancements throughout
the years, with the most recent and important advancement being the development of causal …

paramed performs causal mediation analysis using parametric regression models. Two
models are estimated: a model for the mediator conditional on treatment (exposure) and …

In this paper, we describe the R package mediation for conducting causal mediation
analysis in applied empirical research. In many scientific disciplines, the goal of researchers …

Background: Mediation analyses have been a popular approach to investigate the effect of
an exposure on an outcome through a mediator. Mediation models with multiple mediators …

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 …

The estimation of controlled direct effects can be carried out by fitting a marginal structural
model and using inverse probability of treatment weighting. To use marginal structural …

This paper summarizes recent advances in causal inference and underscores the
paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to …

Background Logistic regression is often used for mediation analysis with a dichotomous
outcome. However, previous studies showed that the indirect effect and proportion mediated …

Researchers often grapple with the idea that an observed relationship may be part of a more
complex chain of effects. These complex relationships are described in terms such as …