How to Plot Interaction Effects in SPSS Using Predicted Values

How to Plot Interaction Effects in SPSS Using Predicted Values. So you've run your general linear model (GLM) or regression and you've discovered that you have interaction effects (i.e. moderating effects). Now what? Next, you might want to plot them to explore the nature of the effects and to prepare them for presentation or publication! The following is a tutorial for who to accomplish this task in SPSS. A follow-up tutorial for how to do this in R is forth coming. To demonstrate this task I'm using one of the sample datasets that comes with SPSS named "demo_cs.sav". To start let's assume that we've already found an interaction effect (see figure below) . In this case, we've run a model in which income and gender are predictive of the price of one's vehicle. The figure below also shows us that income and gender interact to predict price of one's car (p. The significant interaction term indicates that there is a moderating effect to explore graphically! As you may or may not know, the above analysis can be run using either the GLM menu dialog or the regression dialog in SPSS. A key difference between the two is that you'll need to manually create the interaction term using the regression method, whereas the GLM will allow you to specify the interaction in the "Model. " dialog (see 1 in figure below) . Click on the "Model. " button to specify main effects and interactions in a Univariate General Linear Model (GLM). Click on "Plots" to produce effect plots, but this only works for categorical/binary predictors (Fixed Factors). How do you do this when a predictor is continuous? Read on. In the GLM dialog (above) you might've also noticed that there is a "Plots" button that you can click (see 2 in figure above), which seems promising, except you may be disappointed to find that it is only helpful if both predictors are binary or categorical (Fixed Factors in Univariate GLM). If either of the predictors in the interaction you wish to explore graphically are continuous (Covariate in Univariate GLM), then that predictor won't be available to create a plot in the "Plots" dialog (see figure below). Only the "Fixed Factor(s)" predictor is available in the "Univariate: Profile Plots" dialogue. To obtain the plot you are seeking when one of your predictors is continuous (Covariate in Univariate GLM), you simply need to save your predicted values during analysis and plot them using "Graphs > Legacy Dialogs > Scatter/Dot. ". Let's walk through our example. Whether you used the GLM - Univariate analysis or the Regression - Linear analysis the first step is the same: return to your analysis dialog and click on the "Save. " button (GLM - Univariate example on left below, Regression-Linear example on right below). Click "Save. " and then click on the "Unstandardized" box in the "Predicted Values" options.