Nesting in JMP

[#1]

Hi all! I'm having trouble translating the nested structure of my data into the windows for JMP. I have an agricultural fertilizer study, where we have a control (zero fertilizer), and then 10 or so treatments (Fertilizer 1, 2, etc.). Each treatment is at two levels (low and high fertilizer, L and H). So "level" is nested within "treatment". I'm interested in the main treatment effect ("Do fertilizers differ") and whether the low and high rates differ for different fertilizers (e.g., the treatment*level effect). How do I properly code that in JMP? Many thanks in advance!

[#2]

Perhaps I don't understand your question, are you saying that the actual low and high rates are different across the different fertilizers? If the structure is indeed nested, you cannot estimate interaction effects. You write the model as follows: Y = F + R[F]

If they are the same rates, then you have a 10x2 factorial design (plus a control group). In which case you have Y = F + R + F*R.

Since F is categorical, there are no polynomial terms. 

[#3]

Hi @cmc,

Besides the excellent guidance from @statman, you can read the JMP Help section related to nested factors, and more precisely an example with nested factors that will help you define your model (without the random role of the model term): https://www.jmp.com/support/help/en/19.0/#page/jmp/example-of-a-twofactor-nested-random-effects-mode...

Hope this answer may help you,