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The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations
 Journal of Personality and Social Psychology
, 1986
"... In this article, we attempt to distinguish between the properties of moderator 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 moderator and mediator interchangeably by carefully elaborating, both conceptua ..."
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Cited by 5736 (8 self)
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In this article, we attempt to distinguish between the properties of moderator 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 moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately 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 oftenconfused functions of third variables: (a) the moderator function of third variables, which
Psychophysiological and Modulatory Interactions in Neuroimaging
, 1997
"... this paper we introduce the idea of explaining responses, in one cortical area, in terms of an interaction between the influence of another area and some experimental (sensory or taskrelated) parameter. We refer to these effects as psychophysiological interactions and relate them to interactions b ..."
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Cited by 376 (21 self)
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this paper we introduce the idea of explaining responses, in one cortical area, in terms of an interaction between the influence of another area and some experimental (sensory or taskrelated) parameter. We refer to these effects as psychophysiological interactions and relate them to interactions based solely on experimental factors (i.e., psychological interactions), in factorial designs, and interactions among neurophysiological measurements (i.e., physiological interactions) . We have framed psychophysiological interactions in terms of functional integration by noting that the degree to which the activity in one area can be predicted, on the basis of activity in another, corresponds to the contribution of the second to the first, where this contribution can be related to effective connectivity. A psychophysiological interaction means that the contribution of one area to another changes significantly with the experimental or psychological context.Alternatively these interactions can be thought of as a contributiondependent change in regional responses to an experimental or psychological factor. In other words the contribution can be thought of as modulating the responses elicited by a particular stimulus or psychological process. The potential importance of this approach lies in (i) conferring a degree of functional specificity on this aspect of effective connectivity and (ii) providing a model of modulation, where the contribution from a distal area can be considered to modulate responses to the psychological or stimulusspecific factor defining the interaction. Although distinct in neurobiological terms, these are equivalent perspectives on the same underlying interaction. We illustrate these points using a functional magnetic resonance imaging study of attention t...
When moderation is mediated and mediation is moderated
 Journal of Personality and Social Psychology
, 2005
"... Procedures for examining whether treatment effects on an outcome are mediated and/or moderated have been well developed and are routinely applied. The mediation question focuses on the intervening mechanism that produces the treatment effect. The moderation question focuses on factors that affect th ..."
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Cited by 218 (3 self)
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Procedures for examining whether treatment effects on an outcome are mediated and/or moderated have been well developed and are routinely applied. The mediation question focuses on the intervening mechanism that produces the treatment effect. The moderation question focuses on factors that affect the magnitude of the treatment effect. It is important to note that these two processes may be combined in informative ways, such that moderation is mediated or mediation is moderated. Although some prior literature has discussed these possibilities, their exact definitions and analytic procedures have not been completely articulated. The purpose of this article is to define precisely both mediated moderation and moderated mediation and provide analytic strategies for assessing each.
Mapping Cognition to the Brain Through Neural Interactions
 Memory
, 1999
"... Brain imaging methods, such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), provide a unique opportunity to study the neurobiology of human memory. Since these methods can measure most of the brain, it is possible to examine the operations of largescale neura ..."
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Cited by 48 (6 self)
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Brain imaging methods, such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), provide a unique opportunity to study the neurobiology of human memory. Since these methods can measure most of the brain, it is possible to examine the operations of largescale neural systems and their relation to cognition. Two neuroimaging studies, one concerning working memory and the other episodic memory retrieval, serve as examples of application of two analytic methods that are optimized for the quantification of neural systems, structural equation modeling and partial least squares. Structural equation modeling was used to explore shifting prefrontal and limbic interactions from the right to the left hemisphere in a delayed matchtosample task for faces. A feature of the functional network for short delays was strong right hemisphere interactions between hippocampus, inferior prefrontal, and anterior cingulate cortices. At longer delays, these same three areas were strongly linked, but in the left hemisphere, which was interpreted as reflecting change in task strategy from perceptual to elaborate encoding with increasing delay. The primary manipulation in the memory retrieval study was different levels of retrieval success. Partial least squares was used to determine whether the imagewide pattern of covariances of Brodmann areas 10 and 45/47 in right prefrontal cortex (RPFC) and the left hippocampus (LGH) could be mapped on to retrieval levels. Area 10 and LGH showed an opposite pattern of functional connectivity with a large expanse of bilateral limbic cortices that was equivalent for all levels of retrieval as well as the baseline task. However, only during high retrieval area 45/47 was included in this pattern. The results suggest that activ...
Latent variable interaction and quadratic effect estimation: a twostep technique using structural equation.” (http://www.wright.edu/robert.ping/) Updated from Ping R
 Psychological Bulletin
, 1996
"... The author proposes an alternative estimation technique for latent variable interactions and quadraties. Available techniques for specifying these variables in structural equation models require adding variables or constraint equations that can produce specification tedium and errors or estimation d ..."
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Cited by 44 (0 self)
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The author proposes an alternative estimation technique for latent variable interactions and quadraties. Available techniques for specifying these variables in structural equation models require adding variables or constraint equations that can produce specification tedium and errors or estimation difficulties. The proposed technique avoids these difficulties and may be useful for EQS, LISREL 7, and LISREL 8 users. First, measurement parameters for indicator Ioadings and errors of linear latent variables are estimated in a measurement model that excludes the interaction and quadratic variables. Next, these estimates are used to calculate values for the indicator loadings and error variances ofthe interaction and quadratic latent variables. Then, these calculated values are specified as constants in the structural model containing the interaction and quadratic variables. Interaction and quadratic effects are routinely reported for categorical independent variables (i.e., in analysis of variance) frequently to aid in the interpretation of significant main effects. However, interaction and quadratic effects are less frequently reported for continuous independent variables. Researchers have called for the inclusion of interaction and quadratic variables in models with continuous independent
Testing interaction effects in LISREL: Examination and illustration of available procedures
 Organizational Research Methods
, 2001
"... The concomitant proliferation of causal modeling and hypotheses of multiplicative effects has brought about a tremendous need for procedures that allow the testing of moderated structural equation models (MSEMs). The seminal work of Kenny and Judd and Hayduk has been drawn on by several authors in ..."
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Cited by 38 (0 self)
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The concomitant proliferation of causal modeling and hypotheses of multiplicative effects has brought about a tremendous need for procedures that allow the testing of moderated structural equation models (MSEMs). The seminal work of Kenny and Judd and Hayduk has been drawn on by several authors in the past 10 years, thus producing procedures that allow for such tests. Yet, utilization of MSEMs in empirical research has been quite rare. The purposes of this article are twofold. First, the authors discuss general issues with respect to multivariate normality, indicators of latent products, the nature of latent products, and identification problems in MSEM. Second, they review and illustrate techniques that are available for the testing of interaction effects in structural equation models. As the social sciences have developed, the complexity of hypothesized relationships has increased steadily (Cortina, 1993). Two of the more obvious indicators of this complexity are the increasing frequency of hypotheses involving multiplicative effects (e.g., linear interaction effects, nonlinear effects) and the popularity of structural equations modeling (SEM). In spite of the preponderance of both multiplicative effects and
A comparison of approaches for the analysis of interaction eects between latent variables using partial least squares path modeling. Structural Equation Modeling 17
, 2010
"... In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches a ..."
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Cited by 24 (1 self)
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In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches as well as their suitability. This article presents 4 PLSbased approaches: a product indicator approach (Chin, Marcolin, & Newsted, 2003), a 2stage approach (Chin et al., 2003; Henseler & Fassott, in press), a hybrid approach (Wold, 1982), and an orthogonalizing approach (Little, Bovaird, & Widaman, 2006), and contrasts them using data related to a technology acceptance model. By means of a more extensive Monte Carlo experiment, the different approaches are compared in terms of their point estimate accuracy, their statistical power, and their prediction accuracy. Based on the results of the experiment, the use of the orthogonalizing approach is recommendable under most circumstances. Only if the orthogonalizing approach does not find a significant interaction effect, the 2stage approach should be additionally used for significance test, because it has a higher statistical power. For prediction accuracy, the orthogonalizing and the product indicator approach provide a significantly and substantially more accurate prediction than the other two approaches. Among these two, the orthogonalizing approach should be used in case of small sample size and
The path analysis controversy: A new statistical approach to strong apWALLER AND MEEHL336 praisal of verisimilitude
 Psychological Methods
, 2002
"... A new approach for using path analysis to appraise the verisimilitude of theories is described. Rather than trying to test a model’s truth (correctness), this method corroborates a class of path diagrams by determining how well they predict intradata relations in comparison with other diagrams. The ..."
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Cited by 19 (5 self)
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A new approach for using path analysis to appraise the verisimilitude of theories is described. Rather than trying to test a model’s truth (correctness), this method corroborates a class of path diagrams by determining how well they predict intradata relations in comparison with other diagrams. The observed correlation matrix is partitioned into disjoint sets. One set is used to estimate the model parameters, and a nonoverlapping set is used to assess the model’s verisimilitude. Computer code was written to generate competing models and to test the conjectured model’s superiority (relative to the generated set) using diagram combinatorics and is available on the Web
Designing, testing, and interpreting interactions and moderator effects in family research
 Journal of Family Psychology
, 2005
"... This article is a primer on issues in designing, testing, and interpreting interaction or moderator effects in research on family psychology. The first section focuses on procedures for testing and interpreting simple effects and interactions, as well as common errors in testing moderators (e.g., te ..."
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Cited by 18 (0 self)
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This article is a primer on issues in designing, testing, and interpreting interaction or moderator effects in research on family psychology. The first section focuses on procedures for testing and interpreting simple effects and interactions, as well as common errors in testing moderators (e.g., testing differences among subgroup correlations, omitting components of products, and using median splits). The second section, devoted to difficulties in detecting interactions, covers such topics as statistical power, measurement error, distribution of variables, and mathematical constraints of ordinal interactions. The third section, devoted to design issues, focuses on recommendations such as including reliable measures, enhancing statistical power, and oversampling extreme scores. The topics covered should aid understanding of existing moderator research as well as improve future research on interaction effects.
Mediators and moderators in metaanalysis: There’s a reason we don’t let dodo birds tell us which psychotherapies should have prizes
 Journal of Consulting & Clinical Psychology
, 1991
"... In primary studies, psychotherapy researchers frequently search for mediator and moderator variables that can help them understand the relationship between treatment and outcome. Yet a review of past psychotherapy metaanalyses r vealed that none examined the possible role of mediator variables; an ..."
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Cited by 16 (2 self)
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In primary studies, psychotherapy researchers frequently search for mediator and moderator variables that can help them understand the relationship between treatment and outcome. Yet a review of past psychotherapy metaanalyses r vealed that none examined the possible role of mediator variables; and although all of them searched for moderators of study outcome, that search was generally not as complete as it could have been. This article illustrates methods for studying such mediator and moderator variables in metaanalysis, discusses their advantages and disadvantages, and shows how the inclusion of these variables can change interpretation fmetaanalytic results. In particular, the perennial interpretation of past psychotherapy metaanalyses that therapeutic orientation makes no difference to outcomeor asthe dodo bird put it: "Everyone has won and all must have prizes'may be wrong. Orientation may make significant difference, but only by virtue of its moderating and mediating effects. To the best of our knowledge, all metaanalyses ver done have concluded that (on the average) clients receiving psychotherapy do better than clients not receiving psychotherapy. In fact, the computation of average therapy effects over studies is