Reuben M. Baron and Dav id A. Kenny
University of Connecticut
In this article, we attempt to distinguish between the properties ofmoderator and mediator variables
at a number of levels. First, we seek to make theorists and researchers aware of the importance of
not using the terms interchangeably carefully elaborating, both concep-
tually and strategically, the many ways in which moderators and mediators differ. We then go beyond
this largely pedagogical function and delineate he conceptual nd strategic implications ofmaking
use of such distinctions with regard to a wide range of phenomena, including control and stress,
attitudes, and personality raits. We also provide aspecific ompendium ofanalytic procedures ap-
propriate for making the most effective use of the moderator and mediator distinction, both sepa-
rately and in terms of a broader causal system that includes both moderators and mediators.
The purpose of this analysis is to distinguish between the
properties of moderator and mediator variables in such a way
as to clarify the different ways in which conceptual variables
may account for differences in peoples' behavior. Specifically,
we differentiate between two often-confused functions of third
variables: (a) the moderator function of third variables, which
partitions a focal independent variable into subgroups that es-
tablish its domains of maximal effectiveness in regard to a given
dependent variable, and (b) the mediator function of a third
variable, which represents he generative mechanism through
which the focal independent variable is able to influence the
dependent variable of interest.
Although these two functions of third variables have a rela-
tively long tradition in the social sciences, it is not at all uncom-
mon for social psychological researchers to u , the terms
interchangeably. For example, Harkins,
Latan6, and Williams 0980) first summarized the impact of
identifiability on social oafing by observing that it "moderates
social loafing" (p. 303) and then within the same paragraph
proposed "that identifiability is an important mediator of social
loafing:' Similarly, Findley and Cooper (1983), intending a
moderator interpretation, labeled gender, age, race, and socio-
economic level as mediators of the relation between locus of
control and academic achievement. Thus, one largely pedagogi-
This research was supported inpart by National Science Foundation
Grant BNS-8210137 and National Institute of Mental Health Grant
R01 MH-40295-01 to the second author. Support was also given to him
during his sabbatical year (1982-83) by the MacArthur Foundation at
the Center for Advanced Studies in the Behavioral Sciences, Stanford,
California.
Thanks are due to Judith Harackiewicz, Charles Judd, Stephen West,
and Harris Cooper, who provided comments on an earlier version of
this article. Stephen P. Needel was instrumental in the beginning stages
of this work.
Correspondence concerning this article should be addressed toReu-
ben M. Baron, Department ofPsychology U-20, University of Connect-
icut, Storrs, Connecticut 06268.
cal function of this article is to clarify for experimental re-
searchers the importance of respecting these distinctions.
This is not, however, the central thrust of our analysis. Rather,
our major emphasis i on contrasting the moderator-mediator
functions in ways that delineate the implications of this distinc-
tion for theory and research. We focus particularly on the
differential implications for choice of experimental design, re-
search operations, and plan of statistical nalysis.
We also claim that there are conceptual implications of the
failure to appreciate the moderator-mediator distinction.
Among the issues we will discuss in this regard are missed op-
portunities to probe more deeply into the nature of causal
mechanisms and integrate seemingly irreconcilable theoretical
positions. For example, it is possible that in some problem areas
disagreements about mediators can be resolved by treating cer-
tain variables as moderators.
The moderator and mediator functions will be discussed at
three levels: conceptual, strategic, and statistical. To avoid any
misunderstanding of the moderator-mediator distinction by er-
roneously equating it with the difference between experimental
manipulations and measured variables, between situational nd
person variables, or between manipulations and verbal self-re-
ports, we will describe both actual and hypothetical examples
involving a wide range of variables and operations. That is,
moderators may involve either manipulations or assessments
and either situational or person variables. Moreover, mediators
are in no way restricted to verbal reports or, for that matter, to
individual-level variables.
Finally, for expository reasons, our analysis will initially
stress the need to make clear whether one is testing a moderator
or a mediator type of model. In the second half of the article,
we provide a design that allows one to test within the structure
of the same study whether a mediator or moderator interpreta-
tion is more appropriate.
Although these issues are obviously important for a large
number of areas within psychology, we have targeted this article
for a social psychological udience because the relevance of this
distinction is highest in social psychology, which uses experi-
1173

THE MODERATOR-MEDIATOR DISTINCTION 1175
tor is a continuous variable and the independent variable is a
categorical variable; and in Case 4, both variables are continu-
ous variables. To ease our discussion, we will assume that all the
categorical variables are dichotomies.
Case 1
This is the simplest case. For this case, a dichotomous inde-
pendent variable's effect on the dependent variable varies as a
function of another dichotomy. The analysis is a 2  2 ANOVA,
and moderation is indicated by an interaction. We may wish to
measure the simple ffects of the independent variable across
the levels of the moderator (Winer, 1971, pp. 435-436), but
these should be measured only if the moderator and the inde-
pendent variable interact to cause the dependent variable.
Case 2
Here the moderator isa dichotomy and the independent vari-
able is a continuous variable. For instance, gender might moder-
ate the effect of intentions on behavior. The typical way to mea-
sure this type of moderator effect is to correlate intentions with
behavior separately for each gender and then test the difference.
For instance, virtually all studies of moderators of the attitude-
behavior relation use a correlational test.
The correlational method has two serious deficiencies. First,
it presumes that the independent variable has equal variance at
each level of the moderator. For instance, the variance of inten-
tion must be the same for the genders. If variances differ across
levels of the moderator, then for levels of the moderator with
less variance, the correlation of the independent variable with
the dependent variable tends to be less than for levels of the
moderator with more variance. The source of this difference is
referred to as a restriction in range (McNemar, 1969). Second,
if the amount of measurement error in the dependent variable
varies as a function of the moderator, then the correlations be-
tween the independent and dependent variables will differ spuri-
ously.
These problems illustrate that correlations are influenced by
changes in variances. However, regression coefficients are not
affected by differences in the variances of the independent vari-
able or differences in measurement error in the dependent vari-
able. It is almost always preferable to measure the effect of the
independent variable on the dependent variable not by correla-
tion coefficients but by unstandardized (not betas) regression
coefficients (Duncan, 1975). Tests of the difference between re-
gression coefficients are given in Cohen and Cohen (1983, p.
56). This test should be performed first, before the two slopes
are individually tested.
If there is differential measurement error in the independent
variable across levels of the moderator, bias results. Reliabilities
would then need to be estimated for the different levels of the
moderator, and slopes would have to be disattenuated. This can
be accomplished within the computer program LISREL-VI
(J6reskog & S6rbom, 1984) by use of the multiple-group op-
tion. The levels of the moderator are treated as different groups.
Case 3
In this case, the moderator is a continuous variable and the
independent variable is a dichotomy. For instance, the indepen-
Figure 2. Three different ways in which the moderator changes th effect
of the independent variable on the dependent variable: linear (top), qua-
dratic (middle), and step (bottom).
dent variable might be a rational versus fear-arousing attitude-
change message and the moderator might be intelligence as
measured by an IQ test. The fear-arousing message may be
more effective for low-IQ subjects, whereas the rational message
may be more effective for high-IQ subjects. To measure modera-
tor effects in this case, we must know a priori how the effect of
the independent variable varies as a function of the moderator.
It is impossible to evaluate the general hypothesis that the effect
of the independent variable changes as a function of the moder-
ator because the moderator has many levels.
Figure 2 presents three idealized ways in which the modera-
tor alters the effect of the independent variable on the dependent
variable. First, the effect of the independent variable on the de-
pendent variable changes linearly with respect to the moderator.
The linear hypothesis represents a gradual, steady change in the
effect of the independent variable on the dependent variable as
the moderator changes. It is this form of moderation that is gen-
erally assumed. The second function in the figure is a quadratic
function. For instance, the fear-arousing message may be more
generally effective than the rational message for all low-IQ sub-
jects, but as IQ increases, the fear-arousing message loses its ad-
vantage and the rational message ismore effective.
The third function in Figure 2 is a step function. At some
critical IQ level, the rational message becomes more effective
than the fear-arousing message. This pattern is tested by dichot-
omizing the moderator at the point where the step is supposed
to occur and proceeding as in Case 1. Unfortunately, theories
in social psychology are usually not precise enough to specify
the exact point at which the step in the function occurs.
The linear hypothesis tested by adding the product of the
moderator and the dichotomous independent variable to the re-