plot.mediate
(Package: mediation) :
Plotting Indirect, Direct, and Total Effects from Mediation Analysis
Function to plot results from mediate. The vertical axis lists indirect, direct, and total effects and the horizontal axis indicates the respective magnitudes. Most standard options for plot function available.
plot.mediations
(Package: mediation) :
Plotting Indirect, Direct, and Total Effects from Multiple Mediation Analyses
Function to plot results from multiple causal mediation analyses conducted via the mediations funciton. Output is a series of plots generated via plot.mediate for each treatment/mediator/outcome combination specified in the input 'mediations' object.
mediate.sed
(Package: mediation) :
Estimating Average Causal Mediation Effects under the Single Experiment Design
'mediate.sed' estimates average causal mediation effects for the single experiment design. The two options are to use either the sequential ignorability (SI) assumption in which nonparametric estimates of the average causal mediation effect are produced, or, to relax the SI assumption and to calculate the nonparametric bounds on the average causal mediation effect.
ivmediate
(Package: mediation) :
Causal Mediation Analysis with Treatment Noncompliance
'ivmediate' is used to estimate local average causal mediation effects, local average natural direct effects and local average treatment effects for compliers using the method of Yamamoto (2013).
Function to report results from mediation analysis. Reported categories are mediation effect, direct effect, total effect, and proportion of total effect mediated. All quantities reported with confidence intervals. If the treatment-mediator interaction is allowed in the mediation analysis, effects are reported separately for the treatment and control conditions as well as the simple averages of these effects are displayed at the bottom of the summary table.
multimed
(Package: mediation) :
Estimation and Sensitivity Analysis for Multiple Causal Mechanisms
'multimed' is used for causal mediation analysis when post-treatment mediator-outcome confounders, or alternative mediators causally preceding the mediator of interest, exist in the hypothesized causal mechanisms. It estimates the average causal mediation effects (indirect effects) and the average direct effects under the homogeneous interaction assumption based on a varying-coefficient linear structural equation model. The function also performs sensitivity analysis with respect to the violation of the homogenous interaction assumption. The function can be used for both the single experiment design and the parallel design.
The 'summary.mediations' function produces a summary of results from multiple causal analyses conducted via mediations. Output is a series of summary.mediate outputs for all the treatment/mediator/outcome combinations used in the input 'mediations' object.
providing 
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