# nested fixed effects possible?

#### mmercker

##### Member
Hi,

I investigate a problem via a regression model. Firtsly, I have two different ways to measure my outcome, which I incorporate as a two-level factor variable X. However, each of these methods is again influenced by a factor variable with two levels, but these factor variables differ for each method. Thus, for the level X_1 I have "nested" categorical predictor levels "A_x1 and B_x1" and for the level X_1, I have categorical predictor levels A_x2 and B_x2.

How do I formulate this within a regression model in R? Can I fuse the levels A_x1, B_x1, A_x2, B_x2 to just one factor variable with 4 levels, or does this produce problems, because these levels mutually exclude each other regarding the levels X_1 and X_2?

Thanks!

#### Jake

##### Cookie Scientist
You can use the nesting operator "/".
Let the A vs. B factor be named "AB", and it consist of a column of A and B values. Then you could do:
lm(Y ~ X/AB)

#### mmercker

##### Member
Hi,

thanks already. But what if the number of sublevels exclusively corresponding to level X1 differs from the number of sublevels exclusively corresponding to level X2? Is there any problem if I code just one factor variable (without using the nesting operator), and some of the levels of this variable appear exclusively ion only one level of X?

Thanks

#### Jake

##### Cookie Scientist
I think that should work fine too, as long as the nested variable is "explicitly nested" in X (i.e., you use different labels within each level of X).

#### mmercker

##### Member
Thank you, that was exactly what I wanted to know. I just worried, since such a design with "exclusive" sublevels seems to be extremely unbalanced at a first glance...

#### Jake

##### Cookie Scientist
Well, it is extremely unbalanced. But you gotta work with what you have.