A General Model for Testing Mediation
and Moderation Effects
Amanda J. Fairchild
David P. MacKinnon
Published online: 12 November 2008
Society for Prevention Research 2008
Abstract This paper describes methods for testing media-
tion and moderation effects in a dataset, both together and
separately. Investigations of this kind are especially
valuable in prevention research to obtain information on
the process by which a program achieves its effects and
whether the program is effective for subgroups of individ-
uals. A general model that simultaneously estimates
mediation and moderation effects is presented, and the
utility of combining the effects into a single model is
described. Possible effects of interest in the model are
explained, as are statistical methods to assess these effects.
The methods are further illustrated in a hypothetical
prevention program example.
Relations between variables are often more complex than
simple bivariate relations between a predictor and a criterion.
Rather these relations may be modified by, or informed by,
the addition of a third variable in the research design.
Examples of third variables include suppressors, confound-
ers, covariates, mediators, and moderators (MacKinnon et al.
2000). Many of these third variable effects have been
investigated in the research literature, and more recent
research has examined the influences of more than one third
variable effect in an analysis. The importance of investi-
gating mediation and moderation effects together has been
recognized for some time in prevention science, but
statistical methods to conduct these analyses are only now
being developed. Investigations of this kind are especially
valuable in prevention research where data may present
several mediation and moderation relations.
Previous research has described the differences between
mediation and moderation and has provided methods to
analyze them separately (e.g., Dearing and Hamilton 2006;
Frazier et al. 2004; Gogineni et al. 1995; Rose et al. 2004).
More recent research has presented models to simulta-
neously estimate mediation and moderation to investigate
how the effects work together (e.g., Edwards and Lambert
2007; MacKinnon 2008; Muller et al. 2005; Preacher et al.
2007). A review of the substantive literature illustrates that
few applied research examples have used these models,
however. Although analyzing mediation and moderation
separately for the same data may be useful, as described
later in this paper, simultaneous examination of the effects
is often relevant and allows for the investigation of more
varied, complex research hypotheses.
What Type of Research Questions Can Be Addressed
with the Simultaneous Analysis of Mediation
and Moderation Effects?
“Is the Process By Which a Program Has an Effect
the Same Across Different Types of Participants?”
In prevention and intervention research, the mediation model
has been used to understand the mechanism(s) by which
program effects occur. To determine the generalizability
Prev Sci (2009) 10:87–99
A. J. Fairchild (*)
Department of Psychology, University of South Carolina,
1512 Pendleton St.,
Columbia, SC 29208, USA
D. P. MacKinnon
Research in Prevention Lab, Department of Psychology,
Arizona State University,
P.O. Box 871104, Tempe, AZ 85287-1104, USA