Hi everyone, I have been using REML to derive intercepts and coeficients for each individual in a growth study. So the code is m2 <- lmer(change.wt ~ newwt+(newwt|id), data = grow)
Calling coef(model.lmer) gives a matrix with this information which is what I want. However, as a test I looked at each individual on its own and used a simple linear regression to obtain the same information, then I compared the results. It looks like the REML method doesnt seem to approximate the two parameters as well as using the simple linear regression on each individual separately, as judged by looking at graphs. Indeed, why do the results differ at all? Excuse my naivety if this is a silly question. Thanks to everyone for replying to my previous questions, very much appreciated. Simon Pickett PhD student Centre For Ecology and Conservation Tremough Campus University of Exeter in Cornwall TR109EZ Tel 01326371852 ______________________________________________ [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.
