[Eeglablist] mixed model for EEG data

[Stephen Politzer-Ahles]

Hi Lampros,

I'm not aware of an implementation within EEGLAB, but it is straightforward
to do by hand. You would just need to identify the sample[s] of interest on
each trial and construct a model using trials and subjects as random
effects in addition to whatever fixed effects are associated with those
trials. There are several different ways you could handle multiple
comparisons across channels and timepoints; you could average across
several channels and/or timepoints that were of interest a priori, or you
could include channel/region as a fixed effect in the analysis as is
typically done with ANOVA on EEG data, or you could do a mixed model at
each {channel,timepoint} data point and use the model coefficients to do
spatiotemporal clustering as described in Maris & Oostenveld (2007, Journal
of Neuroscience Methods).

Best,
Steve



Stephen Politzer-Ahles
New York University, Abu Dhabi
Neuroscience of Language Lab
http://www.nyu.edu/projects/politzer-ahles/

On Tue, Jun 16, 2015 at 3:44 PM, Lampros Perogamvros <lambros.pero at gmail.com
> wrote:

> Hi all,
>
> We were just wondering whether you guys ever implemented a mixed model
> analysis for eeg data, and if so how you did it/setup the model? This
> model would be ideal when there are unequal numbers of observations per
> condition, and sometimes 0 observations for a condition for a given
> subject. This model would allow us to use all the data and do statistical
> tests on the individual observations rather than just averaging over all
> the observations for each subject, so it would be much more powerful. Are
> you aware of any such model for EEG?
>
> Thanks!
> Lampros Perogamvros MD
> University of Wisconsin
>
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