mediation.effect.plot: Visualizing mediation effects

View source: R/mediation.effect.plot.R

mediation.effect.plotR Documentation

Visualizing mediation effects

Description

Create a mediation effect plot

Usage

mediation.effect.plot(x, mediator, dv, ylab = "Dependent Variable", 
xlab = "Mediator", main = "Mediation Effect Plot", 
pct.from.top.a = 0.05, pct.from.left.c = 0.05, arrow.length.a = 0.05, 
arrow.length.c = 0.05, legend.loc = "topleft", file = "", pch = 20, 
xlim = NULL, ylim = NULL, save.pdf = FALSE, save.eps = FALSE, 
save.jpg = FALSE, ...)

Arguments

x

vector of the predictor/independent variable

mediator

vector of the mediator variable

dv

vector of the dependent/outcome variable

ylab

y-axis title label

xlab

x-axis title label

main

main title label

pct.from.top.a

figure fine tuning adjustment

pct.from.left.c

figure fine tuning adjustment

arrow.length.a

figure fine tuning adjustment

arrow.length.c

figure fine tuning adjustment

legend.loc

specify the location of the legend

file

file name of the plot to be saved (not necessary)

pch

plotting character

xlim

limits for the x-axis

ylim

limits for the y-axis

save.pdf

TRUE or FALSE if the produced figure should be saved as a PDF file

save.eps

TRUE or FALSE if the produced figure should be saved as an EPS file

save.jpg

TRUE or FALSE if the produced figure should be saved as a JPG file

...

to incorporate options from interval functions

Details

Merrill (1994; see also MacKinnon, 2008; MacKinnon et al., 2007; Sy, 2004) presents a method that involves plotting the indirect effect as the vertical distance between two lines. Fritz and MacKinnon (2008) present a detailed exposition of this method too. Preacher and Kelley (2011) discuss this plotting method and implement their own code, which was also independently done as part of Fritz and MacKinnon (2008).

In this type of plot, the two horizontal lines correspond to the predicted values of Y regressed on X at the mean of X and at one unit above the mean of X. The distance between these two lines is thus \hat{c}. The two vertical lines correspond to predicted values of M regressed on X at the same two values of X. The distance between these lines is \hat{a}. The lines corresponding to the regression of Y on M (controlling for X) are plotted for the same two values of X.

Value

A figure is returned.

Note

Requires raw data.

Author(s)

Ken Kelley (University of Notre Dame; KKelley@nd.edu)

References

Fritz, M. S., & MacKinnon, D. P. (2008). A graphical representation of the mediated effect. Behavior Research Methods, 40, 55–60.

MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. Mahwah, NJ: Erlbaum.

MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation analysis. Annual Review of Psychology, 58, 593–614.

Merrill, R. M. (1994). Treatment effect evaluation in non-additive mediation models. Unpublished dissertation, Arizona State University.

Preacher, K. J., & Kelley, K. (2011). Effect size measures for mediation models: Quantitative and graphical strategies for communicating indirect effects. Psychological Methods, 16, 93–115.

Sy, O. S. (2004). Multilevel mediation analysis: Estimation and applications. Unpublished dissertation, Kansas State University.

See Also

mediation.effect.plot, mediation.effect.bar.plot


MBESS documentation built on Sept. 19, 2022, 5:05 p.m.