Simon Pickett
2006-Aug-15 15:34 UTC
[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
Doran, Harold
2006-Aug-15 15:53 UTC
[R] REML with random slopes and random intercepts giving strange results
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: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Simon Pickett > Sent: Tuesday, August 15, 2006 11:34 AM > To: r-help at 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 at 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. >
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