E1190 CMAJ| OCTOBER 28, 2019| VOLUME 191| ISSUE 43 outcome (so-called “colliders”).
There are many valid scenarios in which identifying and measuring the effect of a mediator …

Mediation analyses are valuable for examining mechanisms underlying an association,
investigating possible explanations for nonintuitive results, or identifying interventions that …

The mediation formula for the identification of natural (in) direct effects has facilitated
mediation analyses that better respect the nature of the data, with greater consideration of …

Epidemiologists are increasingly using natural effects for applied mediation analyses, yet 1
key identifying assumption is unintuitive and subject to some controversy. In this issue of the …

The causal mediation literature has mainly focused on “natural effects” as measures of
mediation, but these have been criticized for their reliance on empirically unverifiable …

Analyses of randomised experiments frequently include attempts to decompose the intention‐
to‐treat effect into a direct and indirect effect, mediated by given intermediaries, with the aim …

Background: Mediation analysis is a powerful tool for understanding mechanisms, but
conclusions about direct and indirect effects will be invalid if there is unmeasured …

Purpose We review statistical methods for assessing the possible impact of bias due to
unmeasured confounding in real world data analysis and provide detailed …

Background: Causal inference continues to be a critical aspect of evaluation research.
Recent research in causal inference for statistical mediation has focused on addressing the …

Mediation hypothesis testing for a large number of mediators is challenging due to the
composite structure of the null hypothesis, H 0: α β= 0 H_0:αβ=0 (α α: effect of the exposure …