For a study that I'm currently conducting I want to know the effect of some of my variables on other variables, which I think should be done by creating interaction variables.

However, I'm not sure how I should test for an effect of variable A on a number of other variables (let's say B up to G). The textbook literature I read explains how to test an interaction variable, but in their example they only test 1 in the model..

So my question is, should I test the impact of variable A on variable B-G by creating a new model every time (one with A*B, then one with A*C and so forth) or can I create one model including all the interaction terms A*B, A*C up to A*G in one go?

I ask because the results differ in both approaches. This seems weird to me because if I was only interested in the interaction effect of, say, A*B, I could conclude that there is an impact, where in the full model there actually doesn't seem to be an impact (or the other way around).

From my previous thread I've learned I should normally include all the variables in one model but because it's about interaction here I'm not so sure how to go about it.

Thanks for any and all help!!