[R] predict lmer

Bert Gunter gunter.berton at gene.com
Wed May 7 19:13:30 CEST 2008


Sorry, my reply below may be too terse. You'll need to also construct the
appropriate design matrix to which to apply the fixef() results to.

If newDat is a data.frame containing **exactly the same named regressor and
response columns** as your original vdata dataframe, and if me.fit.of is
your fitted lmer object as you have defined it below, then

 model.matrix(terms(me.fit.of),newDat) %*% fixef(me.fit.of)

gives your predictions. Note that while the response column in newDat is
obviously unnecessary for prediction (you can fill it with 0's,say), it is
nevertheless needed for model.matrix to work. This seems clumsy to me, so
there may well be better ways to do this, and **I would appreciate
suggestions for improvement.*** 


Cheers,
Bert



-----Original Message-----
From: bgunter 
Sent: Wednesday, May 07, 2008 9:53 AM
To: May, Roel; r-help at r-project.org
Subject: RE: [R] predict lmer

?fixef

gets you the coefficient vector, from which you can make your predictions.

-- Bert Gunter
Genentech

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of May, Roel
Sent: Wednesday, May 07, 2008 7:23 AM
To: r-help at r-project.org
Subject: [R] predict lmer

Hi,
 
I am using lmer to analyze habitat selection in wolverines using the
following model:
 
(me.fit.of <-
lmer(USED~1+STEP+ALT+ALT2+relM+relM:ALT+(1|ID)+(1|ID:TRKPT2),data=vdata,
control=list(usePQL=TRUE),family=poisson,method="Laplace"))
 
Here, the habitat selection is calaculated using a so-called discrete
choice model where each used location has a certain number of
alternatives which the animal could have chosen. These sets of locations
are captured using the TRKPT2 random grouping. However, these sets are
also clustered over the different individuals (ID). USED is my binary
dependent variable which is 1 for used locations and zero for unused
locations. The other are my predictors.
 
I would like to predict the model fit at different values of the
predictors, but does anyone know whether it is possible to do this? I
have looked around at the R-sites and in help but it seems that there
doesn't exist a predict function for lmer???
 
I hope someone can help me with this; point me to the right functions or
tell me to just forget it....
 
Thanks in advance!
 
Cheers Roel
 
Roel May
Norwegian Institute for Nature Research
Tungasletta 2, NO-7089 Trondheim, Norway


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