# cluster statistic on one sample

Gopakumar Venugopalan venug001 at BAMA.UA.EDU
Mon Oct 20 14:27:31 CEST 2008

```Hello everyone, I just finished testing the null across two conditions
using EEGLAB which puts out t-values at various points on the waveform,
and then by exporting values to excel converting them to RMS and
averaging them over left vs right and post vs ant. I have the SPSS
to integrate something like this into all the packages. Off course
since MATLAB is very powerful I suspect that adding the required MANOVA
code into those routines will solve the problem.After that is done, the
mathematical formula for generating the F distribution, and the root of
which is the t distribution can be placed in a separate sheet for a
parametric test, even though the data is non-parametric. We can make
parametric assumptions of our data even though it is non-parametric by
nature. I hand did this using a combination of excel, spss, eeglab, and
scan 4.3 which--runs on a matlab engine and is a commercial product.
A paper by Pascual-Marqui (2002) talks about how the F values in the
dipole fit and Current Density Reconstruction is a pseudo-statistic.
That paper also provides a correction so that they can be used as
parametric values. I wonder if such a correction can be applied to the
non-parametric values here, so that they can be treated and interpreted
as parametric values.
I can see this in my mind by can tweak the c code in MATLAB with some
guidance. Am not a programmer by any strech of imagination.
regards
gopa

Quoting jan-mathijs schoffelen <j.schoffelen at PSY.GLA.AC.UK>:

> message,
>
> What about performing a nonparametric test, based on the bootstrap
> distribution of the beta weights under the null-hypothesis?
> This problem sounds similar to one I came across recently (and which
>
> I still have to write something about on fieldtrip's wiki-page (sorry
>
> Eric)), which has to do with the testing of the significance of the
> F-
> value for interaction in a 2x2 repeated measure anova. Also in this
>
> case, one also wants to test a parametric null-hypothesis, as Eric
> phrased it in his last e-mail. One way to test this (I don't have the
>
> reference at hand), is to test the observed F-statistic against a
> null-distribution, obtained from bootstrapping your data, which you
>
> preconditioned as to impose the null-hypothesis (in the case of an
> anova it would be to remove from each of the observations the mean of
>
> the cell to which the observation belongs). I don't know yet how to
>
> impose the null-hypothesis in the regression case, but would this
> line of thought be a possibility?
> As to a potential implementation: Robert and I are pretty close to
> have the bootstrapping implemented.
>
> Yours,
>
> Jan-Mathijs
>
>
> On Oct 20, 2008, at 11:05 AM, Vladimir Litvak wrote:
>
> > Dear Floris and Eric,
> >
> > Parametric tests at scalp level taking into account spatial
> > relationship between sensors can be done in SPM (with RFT
> correction).
> > That'll require using some low-level functions to convert
> > coefficients to images but in principle shouldn't be that
> difficult.
> >
> > Best,
> >
> >>
> >> On Mon, Oct 20, 2008 at 10:17 AM, Eric Maris
> >> <e.maris at donders.ru.nl> wrote:
> >>> Dear Floris,
> >>>
> >>>
> >>>
> >>>> I have a question about statistical analysis on the sensor
> level.
> >>>> I would like to make use of the cluster size thresholding of
> the
> >>>> clusterrand routine in Fieldtrip. Unfortunately, in the current
> >>>> wrapper, it seems there is no option for a one-sample T-test?
> >>>> There is
> >>>> an activation-baseline test, and a (in)dependent samples test
> >>>> between
> >>>> two conditions, but what I want to do is simply test whether a
> 14
> >>>> (subjects) x 275 (channels) matrix is different from zero,
> >>>> taking into
> >>>> account the spatial relations between adjacent sensors. (The
> data
> >>>> points are regression weights from a multiple-regression
> >>>> analysis, so
> >>>> there's no easy way to split it into two parts.)
> >>>> I assume this should be easy to tweak, but I couldn't come up
> >>>> with any
> >>>> smart ideas how to do it.
> >>>> Anyone any ideas?
> >>>
> >>> I'm afraid that I have to disappoint you, Floris. Your null
> >>> hypothesis is a
> >>> typical parametric null hypothesis; the expected value of some
> >>> (matrix-valued) variable being equal to zero. The null hypothesis
>
> >>> that is
> >>> tested by a nonparametric permutation test is equality across
> >>> experimental
> >>> conditions of the probability distribution from which the
> >>> (condition-specific) data are drawn. Since you have single
> >>> condition only, I
> >>> see no way of applying the theory behind nonparametric
> >>> permutation testing
> >>> (of the type described by Maris & Oostenveld, 2007) to your
> data.
> >>>
> >>> To solve your problem we need a brilliant theoretical insight.
> >>>
> >>>
> >>> Greetings,
> >>>
> >>> Eric
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>>
> >>>>
> >>>> Floris
> >>>>
> >>>> ----------------------------------
> >>>> The aim of this list is to facilitate the discussion between
> >>>> users of the
> >>> FieldTrip
> >>>> toolbox, to share experiences and to discuss new ideas for MEG
>
> >>>> and EEG
> >>> analysis.
> >>>> http://www.ru.nl/fcdonders/fieldtrip.
> >>>
> >>> ----------------------------------
> >>> The aim of this list is to facilitate the discussion between
> >>> users of the FieldTrip  toolbox, to share experiences and to
> >>> discuss new ideas for MEG and EEG analysis. See also http://
> >>> listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/
>
> >>> fcdonders/fieldtrip.
> >>>
> >>>
> >>
> >
> > ----------------------------------
> > The aim of this list is to facilitate the discussion between users
>
> > of the FieldTrip  toolbox, to share experiences and to discuss new
>
> http://listserv.surfnet.nl/
> > archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip.
>
> ----------------------------------
> The aim of this list is to facilitate the discussion between users of
> the FieldTrip  toolbox, to share experiences and to discuss new ideas