mediation (version 1.0)

plot.medsens: Plotting results from sensitivity analysis of mediation effects.

Description

Plots results from medsens function. Y axis plots mediation effect and x-axis plots the error correlation rho. Standard options for plot function available.

Usage

## S3 method for class 'medsens':
plot(x, xlab=NULL, ylab=NULL, xlim=NULL, ylim=NULL, main=NULL, pr.plot=FALSE,...) 
 # ## S3 method for class 'plot.medsens':
print(z)

Arguments

x

Output from medsens function.

xlab

x-axis label.

ylab

y-axis label.

xlim

range for x-axis.

ylim

range for y-axis.

main

main title for graph.

pr.plot

If pr.plot=TRUE then proportion mediated will be plotted.

...

Additional arguments to be passed.

References

Imai, Kosuke, Luke Keele and Dustin Tingley (2009) A General Approach to Causal Mediation Analysis. Imai, Kosuke, Luke Keele and Teppei Yamamoto (2009) Identification, Inference, and Sensitivity Analysis for Causal Mediation Effects.

See Also

See also medsens

Examples

#Example with JOBS II Field experiment
#For illustration purposes simulations set to low number.

#Example with JOBS II Field experiment
data(jobs)


#########################################
#continuous mediator and continuous outcome
#########################################

#fit parametric model
model.m <- lm(job_seek ~ treat + depress1 + econ_hard + sex + age  + occp + marital + nonwhite + educ + income, data=jobs)
model.y <- lm(depress2 ~ treat + job_seek + depress1 + econ_hard + sex + age + occp + marital + nonwhite + educ + income, data=jobs)
#pass model objects through medsens function
sens.cont <- medsens(model.m, model.y, T="treat", M="job_seek", INT=FALSE,  DETAIL=FALSE, sims=1000)
#plot mediation effect and 95plot(sens.cont, main="JOBS", ylim=c(-.2,.2))