Statistics for coherence in a within-subject experiment

[Robert Oostenveld]

Hi Jurij

> option 3. - indepsamplesZcoh is obviously only suitable for a between-
> trial, two-condition experiment

Yes, that is for testing coherence differences between two conditions
within one subject.

> and there are no other options that explicitally say they are used
> for coherence.
>
> So how can one compare 6 conditions for 11 subjects with regards to
> coherence if one imports the Time-Frequency domain data for each
> person into FieldTrip?

In your case you have observed a "value" in 11 subjects, over 6
conditions. That value happens to be coherence, but could as well
have been something else. Since you have manipulated the conditions
with each subject, you can use a dependent-samples test: the observed
values depend on the subject (an example of a dependent-samples test
is a paired-t test).

If the number of trials varies between subjects and/or sessions, it
will be preferable to transform your coherence values to z-scores
manually prior to submitting the values to clusterrandanalysis.

Now about the 6 conditions, am I right that you have a 1x6 factorial
design, or is there more strucure in the design? Do you have a
specific hypothesis about the different conditions? If you only want
to reject the null-hypothesis "the observed value (coherence) is the
same (more accurately: stems from the same distribution) in all my 6
conditions", you would use an omnibus F-statistic, i.e.
'depsamplesF'. It might be that your hypothesis is more specific, or
also in case you find an omnibus effect, then you would probably want
to perform explicit tests between two subsets of your 6 conditions
using a 'depsamplesT' test.

best regards,
Robert