About MLmed

MLmed is a computational macro for SPSS that simplifies the fitting of multilevel mediation and moderated mediation models, including models containing more than one mediator. After the model specification, the macro automatically performs all of the tedious data management necessary prior to fitting the model. This includes within-group centering of lower-level predictor variables, creating new variables containing the group means of lower-level predictor variables, and stacking the data as outlined in Bauer, Preacher, and Gil (2006) and their supplementary material to allow for the simultaneous estimation of all parameters in the model.

The output is conveniently separated by equation, which includes a further separation of between-group and within-group effects. Further, indirect effects, including Monte Carlo confidence intervals around these effects, are automatically provided. The index of moderated mediation (Hayes, 2015) is also provided for models involving level-2 moderators of the indirect effect(s). 

Users interested in detailed explanations of the models fit using MLmed, as well as example analyses, may find Chapters 5-6 of my Thesis helpful (full citation below). Note that the User Guide provided within the MLmed download and the link above is more current and thorough than the documentation provided in the appendix of my thesis. 

Rockwood, N. J. (2017). Advancing the formulation and testing of multilevel mediation and moderated mediation models (Unpublished master’s thesis). The Ohio State University, Columbus, OH.

Download

May, 2019 - MLmed Beta 2 now available. It can be downloaded using the link above. The .zip file contains both the MLmed macro (syntax and point-and-click) and the User Guide, which documents the changes made in the new version (including the ability to add a level-2 moderator of the within- and/or between-group direct effect).

There are currently no plans for future releases of MLmed.

Citation/Resources

Multilevel conditional process modeling and MLmed are discussed within the following journal article:

Hayes, A. F. & Rockwood, N. J. (2020). Conditional process analysis: Concepts, computation, and advances in the modeling of the contingencies of mechanisms. American Behavioral Scientist, 64(1), 19-54. [link]

The following book chapter also discusses multilevel mediation and MLmed:

Rockwood, N. J. & Hayes, A. F. (in press). Multilevel mediation analysis. To appear in A. A. O’Connell, D. B. McCoach, & B. Bell (Eds.), Multilevel Modeling Methods with Introductory and Advanced Applications. Charlotte, NC: Information Age Publishing.