I have two categorical values in an normal linear model and the mean value specification is that they both have an effect but there is no interaction. In R, this was modelled as lm(x~ A + B).
I would now like to test whether one of the factors (A) has an effect at all. I am unsure how to do this. Do I compare my model A + B to the model which only assumes B has an effect (so, a F-test between lm(x ~ A + B) and lm(x ~ B))?
Or, do I compare the model where I assume A does have an effect and compare it to the model where we assume there isn't any effect at all (so, F-test between lm(x ~ A) and lm(x ~ 1))?
What's "best", or what differences are there?