Hi,

Sorry for a basic questions on linear models.

I am trying to adjust raw data for both fixed and mixed effects. The data that I 
output should account for these effects, so that I can use the adjusted data for 
further analysis.

For example, if I have the blood sugar levels for 30 patients, and I know that 
'weight' is a fixed effect and that 'height' is a random effect, what I'd want 
as output is blood sugar levels that have been adjusted for these effects. 


====================
library("lme4")
sugar <- c(1:10,sample(1:100,20))
weight <- 1:30
height <- rep(sample(1:15,15,replace=F),2)

lm.adj <- lmer(sugar ~ weight + (1|height))

adjusted.sugar <- fitted(lm.adj)

=====================

I'm not sure if I'm doing this right...?

thanks!



      
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