Hi folks,

I am new to lme in R, and I have a question regarding to the effect of scale
function on the lme. When I use the function to scale and centre the levels
of the fixed effects (e.g., X and Y; both have two levels) and write them to
new columns:
ex:
dat$cX<-scale(as.numeric(dat$X),center = TRUE, scale = FALSE)
dat$cY<-scale(as.numeric(dat$Y),center = TRUE, scale = FALSE)

and compare the lme of centred model ran on cX and cY with the non-centred
model run on X and Y:

centred.model
<- lmer(quest.ACC~1+cX*cY+(1|Subject)+(1|SetNo),data=dat.Transfer,family='binomial')
non.centred.model<-
lmer(quest.ACC~1+X*Y+(1|Subject)+(1|SetNo),data=dat.Transfer,family='binomial')

I find that the two models give very different results not only for the
intercept of the fixed effect effects (which I can understand), but also on
the variance of the fixed effect coefficients, leading to the huge
differences in some case (interactions emerge).

What is going on?
Baris



-- 
SB Demiral, PhD.
Department of Psychology
7 George Square
The University of Edinburgh
Edinburgh, EH8 9JZ
UK
Phone: +44 (0131) 6503063

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