# plot.CI: Plot the posterior distribution of the indirect effect... In BayesMed: Default Bayesian Hypothesis Tests for Correlation, Partial Correlation, and Mediation

## Description

Plot the posterior distribution of the indirect effect alpha*beta including a 95% credible interval around the mean of the posterior (see Nuijten et al. (2014); Yuan & MacKinnon, 2009).

## Usage

 ```1 2``` ```## S3 method for class 'CI' plot(x,...) ```

## Arguments

 `x` the posterior samples of alpha*beta as obtained from the output of `jzs_medSD`. This is an object of class `CI`. `...` additional arguments to be passed on to the plot method, such as graphical parameters (see `par`).

## Author(s)

Michele B. Nuijten <m.b.nuijten@uvt.nl>, Ruud Wetzels, Dora Matzke, Conor V. Dolan, and Eric-Jan Wagenmakers.

## References

Nuijten, M. B., Wetzels, R., Matzke, D., Dolan, C. V., & Wagenmakers, E.-J. (2014). A default Bayesian hypothesis test for mediation. Behavior Research Methods. doi: 10.3758/s13428-014-0470-2

Yuan, Y., & MacKinnon, D. (2009). Bayesian mediation analysis. Psychological Methods, 14, 301-322.

`jzs_medSD`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```## Not run: # simulate mediational data a <- .5 b <- .6 t_prime <- .3 X <- rnorm(50,0,1) M <- a*X + rnorm(50,0,1) Y <- t_prime*X + b*M + rnorm(50,0,1) # run jzs_med res <- jzs_med(independent=X,dependent=Y,mediator=M) # plot posterior distribution of a*b plot(res\$ab_samples) # print the exact lower and upper boundary of the interval res\$CI_ab ## End(Not run) ```