I have a question on how to model interaction terms including smooths in a GAMM
model (using the mgcv and nlme packages in R).
We have collected longitudinal behavioral and brain imaging data from ~100
subjects across ~6 time points, and I would like to model main effects of age,
sex, brain as well as to-way interaction terms (and maybe three-way interaction
terms), while correcting for education level and taking random effects into
account. Is using the ti() setup the way to do this:
M = gamm(behav ~ ti(age) + sex + education + ti(age, by = sex) + brain +
ti(brain, by = age), random = list(subjectID = ~1+age), data = data)
All help will be appreciated.
Thanks, Louise
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