I was just wondering if you could point me in the right direction. I have a dataset with 5 tree clones planted at 10 different sites, i.e. same clones are replicated twice at different sites.
Site Clone 1 A 2 A 3 B 4 B 5 C 6 C 7 D 8 D 9 E 10 E
At each site each clone is replicated multiple times. Ideally, I would want to know what is the effect of clone on my dependent variable y and whether a site effect is present. To me it looks like an incomplete block design with clone as a fixed effect and site as a random effect (and block). Using lmer from the lme4 package in R, I would specify the model as follows:
lmer(y~clone + (1|site), data=mydata)
Is this a correct way of analyzing this dataset? I could also average by clone over sites and eliminate sites. But this way I will lose potential important information as to whether a site effect is present.
Any pointers are appreciated!