I'm looking for a package operating in the same framework as Andrew Hayes's process macro and supporting multiple mediators.
What R package would you recommend for this kind of analysis? I've come across "mediation" and "MBESS". The latter doesn't seem to support multiple mediators though. And the "mediation" package operates in a different framework (potential outcome framework).
Any suggestions?
Hi,
Kindly see the links for R package for multiple mediation analysis:
http://imai.princeton.edu/research/files/mediationR2.pdf
http://repository.cmu.edu/cgi/viewcontent.cgi?article=1142&context=hsshonors
http://www.da.ugent.be/cvs/pages/en/Presentations/Presentation%20Yves%20Rosseel.pdf
Thanks, great suggestions! Because MBESS doesn't allow for covariates I've been messing around with my own code for a while now. However, lavaan is exactly what I needed! It is easy to use and provides many useful options, I can highly recommend it.
Here is another suggestion you might want to try.
http://cran.r-project.org/web/packages/mediation/index.html
mma: An R Package for Mediation Analysis with Multiple Mediators
Authors:
Qingzhao Yu ,
Bin Li
2022 Answer! Thanks for starting the thread Andreas! This is still relevant, so I though I would update a bit.
One of the most popular packages for mediation and moderation is PROCESS by Hayes - who has written a number of texts and articles on these stats and developed software for SPSS and SAS. There is now an R package here: https://www.processmacro.org/download.html
There is a nice 'how to' for PROCESS in R, here: http://www.regorz-statistik.de/en/mediation_process_for_r.html
The mediation package is also popular with many useful options: https://www.rdocumentation.org/packages/mediation/versions/4.5.0
And, here is a nice page on how to do mediation in R: https://www.r-bloggers.com/2019/08/how-to-do-mediation-scientifically/
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