moderate.mediation:Causal Moderated Mediation Analysis
Causal moderated mediation analysis using the methods proposed by Qin and Wang (2023)
<doi:10.3758/s13428-023-02095-4>. Causal moderated mediation
analysis is crucial for investigating how, for whom, and where
a treatment is effective by assessing the heterogeneity of
mediation mechanism across individuals and contexts. This
package enables researchers to estimate and test the
conditional and moderated mediation effects, assess their
sensitivity to unmeasured pre-treatment confounding, and
visualize the results. The package is built based on the
quasi-Bayesian Monte Carlo method, because it has relatively
better performance at small sample sizes, and its running speed
is the fastest. The package is applicable to a treatment of any
scale, a binary or continuous mediator, a binary or continuous
outcome, and one or more moderators of any scale.
