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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