[R] Contrasts for 2x4 interaction in mixed effects model

[semperparatus]

Your problem seems to be exactly the problem I've been having for the past
week.  So glad to find this thread.
However, when I follow the syntax you used to get around the issue, I still
didn't get the output to work in the way yours did.  I don't believe my
factors are truly nested however (nor your factors: if A, B, C, and D occur
in both levels 1 and 2, the effects would be crossed).

I have a model with the variable condition, and the variable patient
(indicating whether the subject is a patient or control) with repeated
measures per subject, and the following is the model I had: 
MLsd = lmer(H.y.~patient*stance*cond + (1|subj), data=H)

I want to be able to look at the same contrast set up you were interested
in, and compare patient to control at every level of the variable condition
(cond).

*When I tried using the syntax you used with my model:
lmer(H.y.~patient*stance*cond+(cond/patient) + (1|subj), data=H), I got this
result, which seems to be using condition 1 as a part of the baseline. Any
idea how to change that?*

Fixed effects:
                  Estimate Std. Error t value
(Intercept)       0.552594   0.012774   43.26
patient1         -0.005951   0.016989   -0.35
stance2          -0.009010   0.014577   -0.62
cond2            -0.023666   0.007028   -3.37
cond3            -0.015469   0.006948   -2.23
patient1:stance2  0.027988   0.019472    1.44
patient1:cond2    0.015981   0.009977    1.60
patient1:cond3    0.014622   0.009905    1.48

Best,
Rachel
(M.S. candidate frantically working to finish her master's project in the
coming week or so)



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