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
multivariate code, I have been wondering about this for months now how
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>:
> Dear Floris, Eric, Vladimir and all other people reading this
> 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,
> >
> > Vladimir
> >>
> >> 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
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>>
> >>>> Thanks in advance!
> >>>>
> >>>> 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.
> >>>> 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 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
>
> > 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 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 ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/fcdonders/fieldtrip.
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