[R] Linear mixed effects models

[Nathan Weisz]

Hi everyone,

I'm a newbie to R and to linear mixed effects modeling, so please have mercy
:-)
Just wanted to check, whether what I'm doing is alright.

I've collected data concerning tonotopic organization of the auditory cortex
in humans, and I have approximately 1400-1800 data/time points per person
(13 in total). Observations were made how the focus of neuronal activity
changed spatially while processing of a frequency-modulated tone.

Regression analysis was performed for each individual using orthogonal
polynomials ...
regtemp <- lm(tempmat[,j] ~ poly(tempmat[,1],degree=i))
... up to degree = 5.

Based on the median (i.e. over all individuals) adjusted R-square, it could
be seen that a linear approach yielded about .5 adj-R2, adding a quadratic
term increased R2 to about .7 (adding further terms didn't increase adj-R2
in a significant manner).

SO: the next step is to apply a linear mixed effects model of the kind:
        y ~ x + x^2
My data.frame looks something like this:

   Latency medlat Subject
1    124.1     NA       1
2    125.6     NA       1
....
306   573.9  -3.83       1
307   575.3  -3.83       1
....
3000  1859.7  -6.04       2
3001  1861.2  -6.04       2
3002  1862.6  -6.03       2
..... etc. until subject 13

I.e. medlat is the dependent variable, latency my independent variable,
subject is the grouping variable (however I didn't group specifically before
calling lme --> was this wrong?).

There are 23686 observations in total, and depending on the subject some NA.
Following function call was used:
dummy.lme <- lme(medlat ~ poly(Latency, degree = 2), data = dummy,
+ random = ~ Latency | Subject, na.action = na.omit)

Questions:
- Is this approach o.k., or have you lost all your hair already?
- Can one of the lme-experts see if there's something overtly wrong with my
lme-call (especially the fixed and random term)
- I wanted to see how the fits look like for every individual. Using
plot(dummy.lme), I thought this should yield a trellis plot, with each
individual in a separate plot (and fitted line). However it didn't (it was
just a big mess). Any hints?

Thanks for your patience and all the best,

Nathan

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Nathan Weisz
Institute for Clinical Psychology and
Behavioral Neuroscience
University of Konstanz
P.O. Box D25
D - 78467 Konstanz
GERMANY

Tel: +49 (0)7531 88- 4612
Fax: +49 (0)7531 88- 2891
E-mail: Nathan.Weisz at uni-konstanz.de
http://www.clinical-psychology.uni-konstanz.de

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