An embedded and charset-unspecified text was scrubbed... Name: not available URL: <https://stat.ethz.ch/pipermail/r-sig-mixed-models/attachments/20130413/2f4c8e18/attachment.pl>
Solution to fitting -lme4- models with lagged variables
2 messages · Clive Nicholas, Ben Bolker
1 day later
Clive Nicholas <clivelists at ...> writes: [snip]
library(lme4)
dd=transform(Dyestuff,lagY1=c(NA,head(Yield,-1)),
lagY2=c(rep(NA,2),head(Yield,-2)),
lagY3=c(rep(NA,3),head(Yield,-3)))
The stuff below is a little bit redundant: if you use
(fit=lmer(Yield~1+lagY1+lagY2+lagY3+(1|Batch),data=dd,REML=T))
then you don't need the other definitions of the lag variables.
Even more compactly you could define a function:
mylag <- function(x,lag) {
c(rep(NA,lag),head(x,-lag))
}
dd=transform(Dyestuff,lagY1=mylag(Yield,1),
lagY2=mylag(Yield,2),
lagY3=mylag(Yield,3))
It's (IMO) a bit of a pity that the built-in lag() function
only works with the (fairly limited) built-in time-series
functionality in R ...