modeling effects in multiple data frames

I have a question.
Is it possible to model when the data comes from different data-frames 
(lme4 or other)?
I have collected data from several participant at random times (every 
participant having data for cca 300 time points). The problem is that 
every participant have their unique time (which is a predictor). Every 
participant have data stored in a txt file. the idea is to model time 
effect (fixed) and participant variation (random effects). The time span 
is the same for all of the participant, but the sampling was random so 
the exact times differ by participant. To be more specific:

out: outcome variable (300 per participant)
t: time variable (300 per participant)
id: individual (100 for now)

I wood like to model something like:

lme4(out~1+time+time^2+(1+tim3+time^2|id, data=?????)

So 100 data-frames (not exactly, txt files) with 300 data points per 
data-frame. id variable defined by data-frame (txt file used).

Any ideas?

Thanks,

Marko

Marko Ton?i?
Assistant Researcher
University of Rijeka
Faculty of Humanities and Social Sciences
Department of Psychology
Sveu?ili?na Avenija 4, 51000 Rijeka, Croatia