Aug 9, 2015 · 18 What do you plan to do with all these interaction terms? There are several options, which is best will depend on what you are trying to do. If you want to pass the interactions to a …

Aug 31, 2022 · The formula you proposed at the end of your question has an interaction but it also includes redundant terms that will drop out of the model because of perfect collinearity. If you want a …

Oct 6, 2016 · Generally the third and higher order interactions are weak and hard to interpret, so my suggestion is to first look at the main effects and second order interactions.

Dec 20, 2022 · I know that I could use lm(a ~ (b + c + d)^2) in order to get all possible two-way interactions in a model, but I need only the interactions with a single predictor.

Mar 7, 2023 · (There are sometimes reasons to violate marginality by including interactions without their corresponding main effects, but if you're going to do this you should know exactly why you're doing it ...)

Feb 17, 2022 · I've come across somewhat of a confusing topic relating to the syntax of multiple regression with explanatory variables and their interactions. A DataCamp explanation led me to think …

May 24, 2022 · I have a model lm = a ~ b I would like to include c, d , e that represent interactions terms with b => lm = a ~ b + b:c + b:d + b:e. Is there a rapid way to obtain this result without taping...