[R] predict lmer

From: May, Roel <Roel.May_at_nina.no>
Date: Wed, 07 May 2008 16:23:15 +0200


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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