Part 1 outlined one issue in deciding whether to put a categorical predictor variable into Fixed Factors or Covariates in SPSS GLM. That issue dealt with how SPSS automatically creates dummy variables from any variable in Fixed Factors.
There is another key default to keep in mind. SPSS GLM will automatically create interactions between any and all variables you specify as Fixed Factors.
If you put 5 variables in Fixed Factors, you’ll get a lot of interactions. SPSS will automatically create all 2-way, 3-way, 4-way, and even a 5-way interaction among those 5 variables.
That’s a lot of interactions.
In contrast, SPSS GLM doesn’t create by default any interactions between Covariates or between Covariates and Fixed Factors.
So you may find you have more interactions than you wanted among your categorical predictors. And you may have fewer interactions than you need among numerical predictors.
There is no reason to use the default. You can override it quite easily.
Just click on the Model button. Then choose “Custom Model.” You can then choose which interactions you do, or don’t, want in the model.
If you’re using SPSS syntax, simply add the interactions you want to the /Design subcommand.
So think about which interactions you want in the model. And take a look at whether your variables are already dummy coded.
If your choices match the defaults, choosing Covariates or Fixed Factors for your categorical predictors can create a lot less work overriding defaults.
Editor’s Update: If you want to learn in depth how SPSS deals with dummy coding and interactions, how to implement and interpret them, as well as the other options in SPSS GLM, check out our tutorial on Running Regressions and ANCOVAs in SPSS GLM.