[FieldTrip] Nonparametric Satatics Based on "Blair and Karniski 1993" Using FieldTrip

Kamia Kavi kamiakavi at gmail.com
Fri Sep 7 19:17:12 CEST 2018


Dear David,

Thanks for the info.

I've fiddled with FieldTrip a bit and I think (but I'm not sure) that if
cfg.correctm is set to any option other than 'cluster', it does not cluster
across times and channels. But I'm still not sure what option for
cfg.correctm will run Blair&Karniski method.

Thanks for the code and the toolbox. I will check my data later with your
toolbox as well.

Best wishes,

Kamia

On Fri, Sep 7, 2018 at 4:35 PM David Groppe <david.m.groppe at gmail.com>
wrote:

> What you would need to do Kamia is to set the neighbors matrix to the
> identity matrix:
>
> neighbours        = ft_prepare_neighbours(cfg_neighb, dataFC_LP);
>
> That function is described here:
> http://www.fieldtriptoolbox.org/reference/ft_prepare_neighbours
>
>
> And I was wrong with what I initially told you. This will still cluster
> variables across time within single electrodes, so it is not equivalent to
> the Blair & Karniski test. I don't know if there is a way to prevent any
> clustering at all in FieldTrip (perhaps set the neighbour matrix to all
> zeros?).
>
> I have some MATLAB code that implements the Blair & Karniski method:
>
>
> https://www.mathworks.com/matlabcentral/fileexchange/54585-mult_comp_perm_t2-data1-data2-n_perm-tail-alpha_level-mu-t_stat-reports-seed_state?s_tid=prof_contriblnk
>
>
> https://www.mathworks.com/matlabcentral/fileexchange/29782-mult_comp_perm_t1-data-n_perm-tail-alpha_level-mu-reports-seed_state?s_tid=prof_contriblnk
>
> That might be easier to use. It is part of a toolbox for ERP analysis that
> may be useful if you're working with ERPs:
> https://openwetware.org/wiki/Mass_Univariate_ERP_Toolbox
>
> cheers,
>    -David
>
>
>
> On Thu, Sep 6, 2018 at 3:35 PM Kamia Kavi <kamiakavi at gmail.com> wrote:
>
>> Hey David,
>>
>>
>>
>> Thank you very much for your tip as well as your paper. I printed that
>> and will read it tomorrow.
>>
>>
>>
>> Two follow-up questions:
>>
>> 1) So, to not cluster the timepoints/channels, is it enough the change
>> the ‘cfg.correcm’ parameter from ‘cluster’ to ‘no’ and leave the other
>> parameters unchanged?
>>
>>
>>
>> 2) if cfg.correctm = ‘no’ (and, of course, using cfg.method =
>> 'montecarlo'), are significant values (i.e., ones rather than zeros) in
>> stat.mask logical matrix already corrected for multiple comparisons? In
>> other words, can these ‘ones’ in the matrix be considered as statically
>> significant channel/timepoints between two conditions at a certain critical
>> value?
>>
>>
>>
>> Best wishes,
>>
>>
>>
>> Kamia
>>
>> On Thu, Sep 6, 2018 at 7:35 PM David Groppe <david.m.groppe at gmail.com>
>> wrote:
>>
>>> Hi Kamia,
>>>    The cluster-based permutation test implemented by FieldTrip is
>>> similar to the Blair & Karniski method:
>>>
>>> http://www.fieldtriptoolbox.org/tutorial/cluster_permutation_timelock
>>>
>>> If you set the parameters of the test such that no timepoint/electrode
>>> has any neighbours (i.e., you can't form any clusters), than it is
>>> equivalent to the Blair & Karniski method.
>>>
>>> For an explanation of how the cluster-based test differs from Blair &
>>> Karniski, I cover that in this review/tutorial paper:
>>>
>>> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4060794/
>>>
>>> cheers,
>>>    -David
>>>
>>>
>>>
>>> On Thu, Sep 6, 2018 at 10:36 AM Kamia Kavi <kamiakavi at gmail.com> wrote:
>>>
>>>> Dear FieldTrip-ers,
>>>>
>>>> Is there an option in FirldTrip to perform a non-parametric statistics
>>>> as described in Blair and Karniski 1993?
>>>>
>>>> Best wishes,
>>>>
>>>> Kamia
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>>>>
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>>>
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