Dear all, how do I get the residuals from a lme() output objects which are adjusted for fixed AND (!) random effects?
I tried residuals(), but it seems they just give me the residuals adjusted for the fixed effects of the regression model. The model I use is: lme.out <- lme(data=MyDataInLongFormat,fixed= outcome~1, random= ~ 1|individual, correlation=corSymm(form = ~time|individual)) Actually, I use only the intercept in the fixed part of the predictor, and I want to get residuals which are adjusted for the fixed part (intercept) and the random effect, ie to get rid of the correlatedness of individual measures across time. This way I want to get data where I can treat the measures per time point as independent groups. Makes sense? Thanks in advance, Will ______________________________________________ R-help@r-project.org 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.
