**Interpreting Moderator effects in Multiple Regression**

Hi Mariana,

The best way to interpret interaction effects in moderated multiple regression is to plot them. Keep in mind that this result is not *statistically significant* therefore should be interpreted with caution.

The method to plot an interaction is described in detail in the reference given at the end of this post and will provide you (or anyone else) with more in-depth information than I will provide here.

I suggest excel for this as other statistical packages seem to have problems and are not as intuitive.

You need to calculate three values for the IV that you want to act as the moderator (IV2). Deciding on cut-points can be relatively arbitrary or if you have meaningful points within your data I suggest you use those. The common method to decide on cut-points is 1SD above the mean, the mean and 1SD below the mean. Alternatively you can use a low value, the mean value and a high value. Note that the mean value will be 0 as you are using centered values.

Your excel spreadsheet should then be set up to have all possible X values (or at least the X values that you are interested in) in one column that you will refer to:

Predicted Y values

X Zlow Zmean Zhigh

1

2

3

4

5

The predicted Y values are given by using the following formula:

[B1+(B3*Z)]*X + [(B2*Z) + B0]

Where:

B0 = the constant (or intercept)

B1 = the unstandardised B coefficient associated with IV1

B2 = the unstandardised B coefficient associated with IV2

B3 = the unstandardised B coefficient associated with IV1*IV2

Z = your chosen value for the moderator

Once you have finished all you need to do is graph the information!!!

Cohen, J., Cohen, P., West, S., & Aiken, L. (2003). Applied multiple regression/correlation analysis for the behavioural sciences. Mahwah, NJ: Lawrence Erlbaum Associates Inc.