Dear readers, Is it possible to specify a model y=X %*% beta + Z %*% b ; b=(b_1,..,b_k) and b_i~N(0,v^2) for i=1,..,k that is, a model where the random slopes for different covariates are i.i.d., in lmer() and how? In lme() one needs a constant grouping factor (e.g.: all=rep(1,n)) and would then specify: lme(fixed= y~X, random= list(all=pdIdent(~Z-1)) ) , that?s how it's done in the lmeSplines- documentation. Any hints would be greatly appreciated- I'm trying to write a suite of functions that will transform additive models into their mixed-effects representation like lmeSplines but using lmer() instead of lme(). Thank you for your time, Fabian Scheipl
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