Multiple Regression Analysis - Moderator effect

4 important questions on Multiple Regression Analysis - Moderator effect

What is a moderator effect and why is it useful to include this in the analysis?

In a moderator effect, the moderator variable affects the relationship between X and Y in terms of the direction and/or strength. This is useful to increase the research relevance, because we can model boundary conditions of the model. This increases the complexity, but makes it more realistic as well.

What is the procedure adding a moderator effect to the model, when it is a) metric, and b) dichotomous?

A) metric; first add a mean-center variable of the IV and moderator,, and then multiply these. This to avoid multicollinearity.

B) non metric (dichotomous); multiply IV and moderator variable

You also must include all single effects. When IV and Moderator are correlated, what should you do?


And how to assess the effects?

Then assess the quadratic effect.

- View adjusted R2 and the significance of the interaction term.
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Why do you mean center the moderator variable before calculating the interaction term?

You mean center the moderator variable before calculating the interaction term, because this way you can interpret the effect better and you avoid multicollinearity.


With mean-centering you check the IV value at the zero mean of the moderator variable.

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