- interaction effects and moderating effects are not the same, actually A& B may have interaction effect on Y, where as only A has moderating effec on the effect of B on Y.
Nonglak, moderation and interaction are the same. Moderation is often used for continuous moderator (= predictor) variables, while interaction is often used for categorical moderator (= predictor) variables. Moderation (and therefore interaction) effects are symmetric: When A influences the effect of B on Y, then also B influences the effect of A on Y. The distinction between moderator and predictor variable is just theoretical, not statistical.
Regards, Karin
Consider the situation where ANOVA shows that there is significant effect of A& B on y, when conducting a simple factor test, there are 3 possibilities: a) effects of A on Y is different due to B which implies that B = moderator ; b) effects of B on Y is different due to A which implies that A = moderator; or c) both A & B are moderators.
Therefore if one want to study whether A is a moderator on the effects of A on y, he ought not use ANOVA to study interaction effect, and he ought to use SEM to study moderating effect employing multiple group strategy.
Hello there,
Not sure if it is important to indicate superiority of moderation over mediation or the other way around...Theory based research question may at some stage indicate whether you need one or another. Moderation is about 'when' and mediation is more about 'how'.
Regards
Nonglak, moderation and interaction are the same. Moderation is often used for continuous moderator (= predictor) variables, while interaction is often used for categorical moderator (= predictor) variables. Moderation (and therefore interaction) effects are symmetric: When A influences the effect of B on Y, then also B influences the effect of A on Y. The distinction between moderator and predictor variable is just theoretical, not statistical.
Regards, Karin
Adding to what Karen said, epidemiologists use yet another name for interaction: They often call it effect modification.
(I sometimes tell my students that there is a deliberate conspiracy to confuse students by concocting multiple names for the same thing.) ;-)
You might like to have a read of this: https://www.researchgate.net/publication/299598926_Mediation_Moderation_and_Interaction_Definitions_Discrimination_and_some_means_of_testing
Moderation and Interaction, and Interaction Terms are not the same. Interaction terms are one way to operationalise hypotheses of Interaction and hypotheses of moderation. Interaction is not the same as Moderation though as Interaction is a more generic term. For example, specifying the interaction of A and B on C via constructing and multiplicative interaction term results in tests of two hypothesis: the hypotheses that B moderates the A to C relationship and simultaneously the hypothesis that A moderates the B to C relationship. It arguable also tests a third: that there is a "working together" of A and B on C - with no reference to notions of moderation.
Presentation Mediation, Moderation, and Interaction: Definitions, Discrim...
I tend to disagree with Karin Schermelleh-Engel and Bruce Weaver. To my understanding, interaction and moderation are similar but they are not the same. Considering the interpretation of “the significant interaction effect of A & B on Y”: Its interpretation is “the effect of A on Y differs as B varies, and the effect of B on Y differs as A varies”.
In the past, when the researcher gets traditional ANOVA result of significant interaction effects, he must employ ‘a set of single main effect tests’ to get a clear picture in order to interpret the results. At present, after the term ‘moderation’ has been coined, it help us interpreting more clearer. So, if we have an evidence-based research hypothesis that only A is the moderator, we can go straight to analyze the moderation model with SEM, process, etc., without analyzing ANOVA. Moderation model can be applied to both metric and non-metric variables.
I am very much appreciated of all answers, especially the one by Professor Hall, the power point of his I have found significantly informative explanation.
There is a thin line between the two.
"When we say X and Z interact in their effects on an outcome variable Y, and there is no real distinction between the role of X and the role of Z. They are both considered predictor variables. Then we identify this effect as interaction effect. While, in case we have clear distinction between the predictor and moderator variables (on the basis of theory) and we are interested to see the impact of predictor on response (affected by moderator), then this effect is known as moderator. One should carefully choose the term which is more suitable to answer one’s research question."
A detailed discussion (with examples) on my blog http://learnerworld.tumblr.com/ might be helpful.
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