Dear all,

I am trying to create a model for a partial split plot design, with factorial treatments, and repeated measures, and am having difficulty with properly incorporating all of these components. It was recommended to me that I bring this issue to this list-serve, and I would be extremely grateful for any feedback.

Here is a brief outline of the experimental design:

I have 15 plots located randomly in space, each of which is assigned to one of 3 fertilizer treatments (n=5 per treatment). Within each of the plots, I have 12 subplots randomly located, each of which has been assigned to one of 3 clipping treatments (n=4 per treatment, although I have been working with the mean of these 4 reps so it is 1 rep of each clipping treatment per plot). Following an initial clipping, I measured responses (productivity for example) in each subplot over two consecutive years.

I began with the split plot design and the model:

lmer(y~between*within+(1|between:subject)
with fertilizer treatment as my between plots factor, clipping treatment as my within plots factor, and the 15 plots as the subjects.

However this does not account for the repeated measures component. I understood 'year' as an additional within plot factor, and then wondered if I could apply the following additions to the original model:

lmer(y~between*within1*within2+(1|between:subject)
Which looks like
lmer(y~fert*clip*year+(1|fert:plot)

I am new to these models and expect that I am substantially oversimplifying things. Is the above model suitable or fundamentally flawed? If the latter, does anyone have recommendations on how I can amend it or on other alternatives?

Many thanks in advance.

Best regards,

Tara

Department of Biology
Queen's University
Kingston, ON, Canada



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