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 |