[R-sig-ME] time delayed response as a covariate in lme4

[marKo]

I have a dataset which have a continuous outcome variable and a time 
(chron) covariate for 99 subjects (id). To get an idea:

 > str(dataframe)
'data.frame':   36352 obs. of  9 variables:
   $ response  : int  100 79 63 50 71 73 62 72 76 77 ...
  $ id   : Factor w/ 99 levels "g1_1","g1_12",..: 2 2 2 2 2 2 2 2 2 2 ...
  $ time   :Classes 'chron', 'dates', 'times'  atomic [1:36352] 15875 
15875 15875 15875 15875 ...
   .. ..- attr(*, "format")= Named chr [1:2] "m/d/y" "h:m:s"
   .. .. ..- attr(*, "names")= chr [1:2] "dates" "times"
   .. ..- attr(*, "origin")= Named num [1:3] 1 1 1970
   .. .. ..- attr(*, "names")= chr [1:3] "month" "day" "year"

I would like to use the time delayed response as a predictor/covariate. 
Lets say a would like to use response at time-1 as a covariate. How can 
this be done?

Something like (conceptually):

model<-lmer(response~poly(time, n) + response(time -1) + (poly(time, 
n)|id, data=dataframe)

I suppose that I could use some correlation structure for this (in nlme, 
because I think that lme4 do not support this a this stage), although 
I'd rather do this in lme4.

Any ideas?

Cheers (and thanks),

Marko

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