Moderation Analysis

Question 1

When is a moderation analysis utilised?

Answer 1

when there is a moderator variable (= a variable that affects the relationship between 2 others) involved in a model. . It involves an interaction effect between the moderator and the independent variable.

Question 2

What does this mean we need to add to the equation?

Answer 2

Thus, we need to add the combined effect of two or more predictor variables on an outcome to the equation.

Question 3

What does the equation of a moderation with 1 predictor and a moderator look like?

Answer 3

outcome = b0 + (b1X1) + (b2X2) + (b3X1X2) + error.

Or: outcome = b0 + (b1predictor) + (b2moderator) + (b3predictormoderator) + error.

Question 4

What assumptions should be checked for a moderation analysis?

Answer 4

We should check for multicollinearity by performing a regression analysis, with the moderator as a predictor.

Question 5

What is meant by Multicollinearity?

Answer 5

Multicollinearity refers to a situation in which two or more explanatory variables in a multiple regression model are highly linearly related.

Question 6

What is meant by grand mean centering?

Answer 6

the centering of data around a fixed point by subtracting the grandmean from each datapoint.

Question 7

What is the purpose of grand mean centering?

Answer 7

This enables us to make accurate estimations of the regression coefficients when one of the variables in the model can’t take the value zero (such as heartbeat)

Question 8

Where can you find the grand mean centred moderator scores in the output?

Answer 8

The conditional effect of focal predictor at values of the moderator table

Question 9

How can you get the original moderator score?

Answer 9

add the mean of the moderator to the centered score.