Currently I'm trying to analyze data using a mixed model in R.
The data is structured as follows: There are 2 conditions, A and B. For each condition, there are 3 treatments, 1-3. These treatments were done in triplicate, i.e. there are 3 samples per treatment per condition. For each sample, the percentual abundance of a large number of substances were measured (sum of all substances in 1 sample = 100). I am interested in the effect of the treatment in a condition as well as in comparing the treatments between condition for the substances, which means that I would like to know which of the substances have a significantly different concentration between treatments/ conditions.
Thus, I specified my data as a mixed model with lmer:
m <- lmer(logit(abundance)~treatment*condition + (1+treatment*condition|substance), data=d)
Aside from the fact that I am not totally sure whether I specified the random effect structure in the right way, I was wondering how to assess the significance of levels of the random factor. That is, I would like to know which levels are actually significantly different between treatments and/or conditions. Unfortunately I was not able to find anything regarding this. Thus, any help would be greatly appreciated!