modmed                  Causal Moderated Mediation Analysis 'modmed' is
                        used to fit mediator and outcome models and
                        estimate and test causal effects for causal
                        moderated mediation analysis. It is applicable
                        to a treatment of any scale, a binary or
                        continuous mediator and outcome, one or more
                        moderators of any scale, and a wide range of
                        scenarios of moderated mediation.
modmed.plot             Visual Representation of the Causal Moderated
                        Mediation Analysis Results 'modmed.plot' is
                        used to visualize results from 'modmed'
                        function. This applies only if moderators.disc
                        or moderators.cont is not NULL. The plot
                        consists of two parts. The top represents the
                        sampling distribution of the specified causal
                        effect as a function of the specified moderator
                        within the given levels of the other
                        moderators. The bottom represents the
                        distribution of the specified moderator on the
                        x axis.
modmed.sens             Simulation-Based Sensitivity Analysis Table for
                        Causal Moderated Mediation Analysis
                        modmed.sens' is used to evaluate the
                        sensitivity of the estimated causal effects
                        obtained from 'modmed' function to potential
                        violations of the ignorability assumptions from
                        the frequentist perspective. It estimates the
                        causal effects after adjusting for an
                        unmeasured pretreatment confounder, U, with a
                        specified degree of confounding. In a
                        randomized experiment, the degree of
                        confounding is evaluated via two sensitivity
                        parameters, the coefficient of U in the
                        mediator model and that in the outcome model,
                        given the specified prior distribution of U.
                        When the treatment is not randomized, an
                        additional sensitivity parameter is introduced
                        - the coefficient of U in the treatment model.
                        The treatment, mediator, outcome, and
                        unmeasured pretreatment confounder could be
                        either binary or continuous.
newws                   NEWWS Riverside data
sens.plot               Simulation-Based Sensitivity Analysis Plot for
                        Causal Moderated Mediation Analysis
summary_modmed          Summarizing Output for Causal Moderated
                        Mediation Analysis 'summary_modmed' is used to
                        report from causal moderated mediation analysis
