My design goes like this: I have 1 treatment and one control, organized in 3 blocks, each have 1 site of control and 1 site of treatment, each site have 2 subsites, and I sampled 6 quadrats per subsites: 3 under tree canopy, 3 outside tree canopy. This is a repeated measure experiment, with the same sampling method every year. I am interested in comparing treatment vs control over time.
My model goes like this:
lmer(Y ~ Time * Treatment + (1 | Block) + (1 | Site / Subsite)). But I am not sure how to classify the canopy component. Should I include it as a random effect nested in subsite as
(1 | Site / Subsite / Canopy) or on its own as
(1 | Canopy) or as a fixed effect?
(Or can I not include it in the model as I am not interested in it??)