“I'd like to mean center a lot of variables in order to compute interaction terms for a regression analysis. Is there an easy way to do this for many variables simultaneously?”
Mean Centering - What and Why
- This tutorial focuses on mean centering variables in SPSS. However, we'll briefly introduce the concept first.
- Mean centering a variable means subtracting its (arithmetic) mean from all its values.
- The result is that a mean centered variable has a mean of exactly zero. (Apart from that, its frequency distribution does not change.)
- Note that mean centering is also one of the two steps in standardizing variables (computing their z-scores).
- Mean centering without fully standardizing variables is usually done before computing interaction terms in regression analysis.
- Doing so decreases multicollinearity between an interaction term and its corresponding main effects. It may also facilitate the interpretation of regression coefficients for the interaction terms.
SPSS Mean Center ToolSPSS Mean Center Variables Tool
- Make sure you have the SPSS Python Essentials installed.
- Download and install Mean Center Variables. Note this is an SPSS custom dialog.
- Go to . Fill in the names of the variables you’d like to mean center.
- By entering a prefix, mean centered variables will be created as new variables in the active dataset. With the prefix left empty, the original variables will be overwritten by their mean centered counterparts.
- Click syntax. and run the pasted
- As a quick check, you could run
DESCRIPTIVESon the mean centered variables to confirm that they all have zero means.
- Clicking the tool's button will take you to this tutorial. We very much appreciate your feedback on it.