Say we have a variable A (some interaction network metric, continuous, N=20), and we want to see if A varies across B (categorical variable, 2 levels) depending on the levels of a third categorical variable C (3 levels).

So I am interested in exploring whether the differences in my interaction network metrics (A) vary across environmental gradients (B), depending on the way I measure it (C) (i.e. Do I get different results regarding differences to environmental gradient depending on the way y measure it?).

An interaction model tells me the differences between every condition (every level combination) but I just want to know the differences of A against B conditional to the three C levels.

Another option is to calculate the differences between A and B, and use it as the dependent variable to build a model.

Is there another way to model this relationship with the raw data so that I do not have to calculate a new variable?

  • $\begingroup$ Is there any reason you don't want to calculate the difference $B-A$? Maybe you want a symmetric analysis? There are many possibilities, can you tellus what this variables represent in real life? $\endgroup$ Commented Jan 27, 2019 at 15:05
  • $\begingroup$ Your direct approach makes the most sense to me! $\endgroup$
    – user233429
    Commented Jan 27, 2019 at 15:28
  • $\begingroup$ Thank you for your help. I am sorry I made a mistake when I wrote the question (I eddited it). If I calculate the differences before, I think I am losing information. I will only have 10 samples instead of 20 and I will modify the distribution of the errors as far as I know. $\endgroup$
    – Charly
    Commented Jan 28, 2019 at 21:01

1 Answer 1


If your main interest is in the difference, why do you not want to analyze it directly? You should tell us that!

Meanwhile, you should start by making some plots (and show us). Since $C$ is categorical, in practice this could depend on the number of levels of $C$ (one reason we need some context and not only a very abstract problem description.) For the time being assuming not to many levels, some possibilities:

In case your two measurements $A,B$ is pre- and post some intervention or similar, see Best practice when analysing pre-post treatment-control designs

If you give some relevant context I will try to extend.

  • $\begingroup$ Thank you kjetil! I am sorry for the bad formulated question. I eddited the question to provide more information and a best context. I cannot plot the data because I don`t have it yet. $\endgroup$
    – Charly
    Commented Jan 28, 2019 at 21:03

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