[FieldTrip] assessing significance in using ft_timelockanalysis results

[Eric Maris]

Hi Kanal,

> The event related statistics tutorial
> (http://fieldtrip.fcdonders.nl/tutorial/eventrelatedstatistics) talks
about
> assessing significance parametrically by running t-tests on pooled
> timelockanalysis data. My question is, does the fact that the averages
were
> created from N trials make a difference? If I'm condition A has twelve
> averages and condition B has another twelve, and each average contains 70
> trials, is there a way to "inform" the statistical test that the power in
this
> dataset is greater than 24? Is this only possible if I run the t-test
comparing
> each set of 840 (70*12) trials?
> 
> I'm also curious whether this is possible with non-parametric analyses, as
> well. Thanks -

In an analysis over subjects (called random-effects analysis in the fMRI
literature), "informing" the statistical test about the number of trials per
condition only makes sense if this number is different for the two
conditions. I propose that you have a look the fMRI papers that deal with
the issue of fixed-versus-random effect analyses. The conceptual issues
involved are the same in fMRI and electrophysiology.


Best,

Eric Maris




> 
> Elli Kanal
> 
> 
> --------------------
> Eliezer Kanal, Ph.D.
> Postdoctoral Fellow
> Center for the Neural Basis of Cognition
> Carnegie Mellon University
> 4400 Fifth Ave, Suite 110A
> Pittsburgh PA 15213
> P: 412-268-4115
> F: 412-268-5060
> 
> 
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