about cluster randomization analysis

[Marco Buiatti]

Dear FieldTrip Masters,
 thank you again for your clear and rapid answers. Another question about
clusterrandanalysis. As I told you, I'm performing a cluster randomization
test for a within-subject experiment, using a two-sided t-test as pair
statistics. The tutorial says that clustering is performed separately for
thresholded positive and negative t-statistics, and that the critical value
for the cluster level statistics is also two-sided. I understood that the
positive(negative) critical value corresponds to the 95% portion of the
randomization distribution of the maximum(minimum) of the positive(negative)
clusters statistics. Then, why do I obtain two identical (in absolute value)
critical values? What am I missing?
 thank you,
 Marco

 On 11/9/05, Robert Oostenveld <r.oostenveld at fcdonders.ru.nl> wrote:
>
> Hi Marco,
>
> On 8-nov-2005, at 12:25, Marco Buiatti wrote:
> > Do you think it would be correct to slide a relatively large (width
> > of 200ms? 400ms? to be chosen a priori of course) window through
> > the epochs and compute cluster randomization analysis for each
> > latency to explore dubious significant t-test clusters?
>
> You can use such an approach, but then you have to consider each
> position of the window that you are sliding as a seperate statistical
> comparison of the data in the experimental conditions. The multiple
> comparison problem over channels and timepoints within the window is
> then automatically taken care of by clusterrandanalysis, but the
> multiple comparisons that arise due to the multiple locations of the
> window in which you are "interrogating" your data are not treated by
> clusterrandanalysis. That means that, for this approach to be
> statistically completely sound, you should do a Bonferoni correction
> on the alpha threshold, dividing it by the number of window positions.
>
> Probably you will loose a lot of your statistical power especially if
> you slide the window in small steps, so I doubt whether it is
> usefull. Given that you have expressed your doubts about potential
> artifacts in some of your subjects and the influence of the artifacts
> on the outcome of the statistical test, I would guess that putting
> more effort into making the data itself cleaner is probably more
> worthwile.
>
> best regards,
> Robert
>
>
> =======================================================
> Robert Oostenveld, PhD
> F.C. Donders Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> phone: +31-24-3619695
> http://www.ru.nl/fcdonders/
>



--
Marco Buiatti - Post Doc

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