I don't this is because you are using REML. The BLUPs from a mixed model experience some shrinkage whereas the OLS estimates would not.
> -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Simon Pickett > Sent: Tuesday, August 15, 2006 11:34 AM > To: r-help@stat.math.ethz.ch > Subject: [R] REML with random slopes and random intercepts > giving strange results > > 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 > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > ______________________________________________ R-help@stat.math.ethz.ch 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.