I am currently running a logistic regression model in order to analyze my transaction data. Unfortunately I do find contrary recomendations regarding the testing of moderators (btw, some use the term interaction effect, is this really the same?).
My approach looks like this:
1) Generate a new variable (if you can justify this by the literature or by observed confounding) which represents the product of the potential moderator and the respective independent variable
2) Include the new variable into the model - next to all the direct effects
3) If the wald test is significant, the moderating role is proved.
My question: Is this process correct? Other sources recommend to split the sample into two or more groups (with strong and weak/no influence of the moderator.
Thank you very much!