[R-sig-ME] modeling effects in multiple data frames

[Emmanuel Curis]

Assuming your hundred data.frames are in a list called data, why not
simply join them in a single data.frame: something like

d <- do.call( rbind, data )

This should work if all your data.frames (text files) have the same
number of variables and the same names for them.

Hope this helps,

On Tue, Jul 16, 2013 at 12:56:29PM +0200, marKo wrote:
« 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 Tončić
« Assistant Researcher
« University of Rijeka
« Faculty of Humanities and Social Sciences
« Department of Psychology
« Sveučilišna Avenija 4, 51000 Rijeka, Croatia
« 
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« R-sig-mixed-models at r-project.org mailing list
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-- 
                                Emmanuel CURIS
                                emmanuel.curis at parisdescartes.fr

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