View source: R/mediation.effect.bar.plot.R
| mediation.effect.bar.plot | R Documentation |
Provides an effect bar plot in the context of simple mediation.
mediation.effect.bar.plot(x, mediator, dv,
main = "Mediation Effect Bar Plot", width = 1, left.text.adj = 0,
right.text.adj = 0, rounding = 3, file = "", save.pdf = FALSE,
save.eps = FALSE, save.jpg = FALSE, ...)
x |
vector of the predictor/independent variable |
mediator |
vector of the mediator variable |
dv |
vector of the dependent/outcome variable |
main |
main title |
width |
width of bar, default 1 |
left.text.adj |
for fine tuning left side text adjustment |
right.text.adj |
for fine tuning right side text adjustment |
rounding |
how to round so that the values displayed in the plot do not have too few or too many significant digits |
file |
file name of the plot to be saved (not necessary) |
save.pdf |
|
save.eps |
|
save.jpg |
|
... |
optional additional specifications for nested functions |
Provides an effect bar for mediation (Bauer, Preacher, & Gil, 2006) may be used to plot the results of a mediation analysis compactly. Effect bars represent, in a single metric, the relative magnitudes of several values that are important for interpreting indirect effects. Preacher and Kelley (2011) discuss this plotting method also.
Only a figure is returned
Ken Kelley (University of Notre Dame; KKelley@nd.edu)
Bauer, D. J., Preacher, K. J., & Gil, K. M. (2006). Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: New procedures and recommendations. Psychological Methods, 11, 142–163.
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.
mediation, mediation.effect.bar.plot
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