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Nesting random effect inside continuous effect

I'm trying to set up an analysis where I want to do linear regression on a fixed effect, say tablet weight.  I am running an assay where I take several tablets of weight 20 and 40.  The assays are random, say 1-5.  To make things a bit more complicated, within each assay there are several aliquots that serve as subsamples or observations.  I think the model is

Y(i,j,k) = b_0 + B_1 * W(i) + A(j) + E(k[i,j])

where A (assay) is random and nested in W

E is random and nested in W and A.

I understand that I can set up W as nominal and get the correct model and then, off-line, figure out the slope and intercept.  But why is this model considered invalid in JMP.  JMP says I can't have nested continuous terms.


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