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 -- Echte DSL-Flatrate dauerhaft für 0,- Euro*. Nur noch kurze Zeit! ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
