[Eeglablist] Codes for cluster correction are needed

Dr Cyril, Pernet wamcyril at gmail.com
Thu Jul 21 02:22:05 PDT 2022


Hi Olivia,

You can in principle do clustering under 1 dimension only using 
https://urldefense.com/v3/__https://github.com/LIMO-EEG-Toolbox/limo_tools/blob/master/limo_clustering.m__;!!Mih3wA!BrNn2j4iKMeFLS6PS8IC6f7nRqK9ye2CG39s_8-u6R209tyg6NpxXExCVvR9z9g0EU9_RjUBrWmEr2UUzu6Ayw$  
- but you will have to generate the bootstrap or permutation data under 
the null. I am really not sure that this would be less conservative than 
FDR in such a case though.

Cyril


> Hi Cyril,
>
> Thank you very much for your kind reply with detailed explanations!
>
> However, FDR correction is too conservative in my case. So, I’d like to use alternative correction methods that can take space information into consideration.
>
> I thought it would be easy to finish cluster corrections for peak amplitude statistics in EEGLAB. But it looks like not.
>
> Best wishes,
> Olivia
>
> ------- Original Message -------
> On Wednesday, July 20th, 2022 at PM 3:18, Dr Cyril, Pernet <wamcyril at gmail.com> wrote:
>
>
>> Hi Olivia
>>
>> clustering requires some continuity over space and/or time - here you
>> have a 30 (Subjects) × 4 (Conditions in my experiment) × 66 (Channels)
>> matrix of peak values so could cluster over space but I would really not
>> recommend doing that as these a 'peaks' so really different measurements
>> at each channels - in your case I'd test whatever differences you are
>> interested in and apply an FDR correction.
>>
>> more info from a good old EEGLAB lecture
>> https://urldefense.com/v3/__https://figshare.com/articles/presentation/Statistical_analysis_of_EEG_data_Hierarchical_modelling_and_multiple_comparisons_correction/4233977__;!!Mih3wA!BrNn2j4iKMeFLS6PS8IC6f7nRqK9ye2CG39s_8-u6R209tyg6NpxXExCVvR9z9g0EU9_RjUBrWmEr2Wvu8_cjQ$ 
>> slides 2 and 3 gives you an idea why I'd not recommend your approach
>> above and slides 24+ explains multiple comparison corrections and among
>> those procedure, clustering.
>>
>> reference article
>> https://urldefense.com/v3/__https://www.sciencedirect.com/science/article/pii/S0165027014002878__;!!Mih3wA!BrNn2j4iKMeFLS6PS8IC6f7nRqK9ye2CG39s_8-u6R209tyg6NpxXExCVvR9z9g0EU9_RjUBrWmEr2WxKJjPFg$ 
>>
>> cyril
>>
>>> Dear EEGLAB geniuses,
>>>
>>> Do you know whether there are codes for performing cluster corrections?
>>>
>>> After I finished the preprocessing analysis in EEGLAB, I picked out peak values of N170 from average waveforms through custom Matlab codes. And a 30 (Subjects) × 4 (Conditions in my experiment) × 66 (Channels) matrix of peak values was generated. Afterwards, I conducted repeated measure ANOVA and got statistical values of each channel.
>>>
>>> Now I need to perform multiple comparison corrections (cluster correction) for the comparison of peak value difference among the four conditions. Are there codes or more effortless ways that can help me?
>>>
>>> Looking forward to your reply!
>>>
>>> Cheers!
>>>
>>> Best regards,
>>>
>>> Olivia
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>>
>> --
>> Dr Cyril Pernet, PhD, OHBM fellow, SSI fellow
>> Neurobiology Research Unit,
>> Building 8057, Blegdamsvej 9
>> Copenhagen University Hospital, Rigshospitalet
>> DK-2100 Copenhagen, Denmark
>>
>> wamcyril at gmail.com
>> https://urldefense.com/v3/__https://cpernet.github.io/__;!!Mih3wA!BrNn2j4iKMeFLS6PS8IC6f7nRqK9ye2CG39s_8-u6R209tyg6NpxXExCVvR9z9g0EU9_RjUBrWmEr2UdSb0_VA$ 
>> https://urldefense.com/v3/__https://orcid.org/0000-0003-4010-4632__;!!Mih3wA!BrNn2j4iKMeFLS6PS8IC6f7nRqK9ye2CG39s_8-u6R209tyg6NpxXExCVvR9z9g0EU9_RjUBrWmEr2Vu9feMUA$ 

-- 
Dr Cyril Pernet, PhD, OHBM fellow, SSI fellow
Neurobiology Research Unit,
Building 8057, Blegdamsvej 9
Copenhagen University Hospital, Rigshospitalet
DK-2100 Copenhagen, Denmark

wamcyril at gmail.com
https://urldefense.com/v3/__https://cpernet.github.io/__;!!Mih3wA!BrNn2j4iKMeFLS6PS8IC6f7nRqK9ye2CG39s_8-u6R209tyg6NpxXExCVvR9z9g0EU9_RjUBrWmEr2UdSb0_VA$ 
https://urldefense.com/v3/__https://orcid.org/0000-0003-4010-4632__;!!Mih3wA!BrNn2j4iKMeFLS6PS8IC6f7nRqK9ye2CG39s_8-u6R209tyg6NpxXExCVvR9z9g0EU9_RjUBrWmEr2Vu9feMUA$ 




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