[FieldTrip] Regression of behavioral data against EEG data

[Ulrich Pomper]

Dear list,

I believe the original question was referring to the p-values of the 
beta coefficients.

At the first level analysis, regression results in beta coefficients, 
but also in t/ p-values of those coefficients (whether the slope differs 
significantly from zero) and in r values (how much variance is explained 
by the predictor). It is likely, that oftentimes beta values might be 
large at the single subject level, even though they are not 
significantly different from zero, or not explaining a lot of the 
variance in the data.

Despite that, most analyses (that I have seen so far) seem to favour 
betas over r or p values for second level analyses. I would alse be very 
interestd in why that is the case, and how the interpretation of the 
data would differ if instead the explained variance or the p values 
(from single subjects) would be used for group level statistics.

Best wishes,

Ulrich

Am 12.12.2022 12:24, schrieb Ivaylo Iotchev via fieldtrip:

> Interpreting and averaging p-values is not the same thing. P-values 
> answer a very specific question and are the last step of any inquiry, 
> all averaging, separation, other combinations of data happen before a 
> p-value is calculated.
> 
> Am Mo., 12. Dez. 2022 um 11:35 Uhr schrieb Burcu Bayram via fieldtrip 
> <fieldtrip at science.ru.nl>:
> 
>> Thank you very much for your reply!
>> 
>> Would you be so kind to elaborate on why interpreting or averaging
>> r-squared values or p-values does not make much sense?  And why
>> r-squared values give a very reasonable topography, but one that is so
>> much different from the topography of beta values?
>> 
>> Best regards,
>> Burcu
>> 
>> On 12.12.2022 08:18, Schoffelen, J.M. (Jan Mathijs) via fieldtrip 
>> wrote:
>>> Hi Burcu,
>>> 
>>> Conventially, the parameter estimates (i.e. the beta weights) are
>>> taken to the second level for an inferential statistical test.
>>> Averaging p-values, or r-squared values is usually not done, and also
>>> does not make much sense.
>>> 
>>> Best wishes,
>>> Jan-Mathijs
>>> 
>>> 
>>>> On 10 Dec 2022, at 17:07, Burcu Bayram via fieldtrip
>>>> <fieldtrip at science.ru.nl> wrote:
>>>> 
>>>> Dear FieldTrip community,
>>>> 
>>>> I'm new to regression analysis of EEG data and unsure which 
>>>> regression
>>>> outputs to use. Beta-coefficients give a very different pattern of
>>>> results compared to r squared values or p-values, although all of 
>>>> them
>>>> (to my understanding) should express a form of relation between the
>>>> two datasets. We are looking for help regarding the interpretation 
>>>> of
>>>> those data and which one to select for our analysis. In our model,
>>>> behaviour is the predictor and EEG activity is the outcome. The
>>>> datapoints for each are single experimental trials (~2000 per
>>>> subject).
>>>> So far, we just used simple linear regression, but the plan is to 
>>>> use
>>>> multiple linear regression at a later stage.
>>>> The idea is to plot and interpret the regression results as if they
>>>> were EEG amplitudes. So we get a time course and a topography of
>>>> regression results, that help us to determine where and when in the
>>>> brain behavior predicts neural activity. Our main questions are:
>>>> 
>>>> 1. Which value makes most sense to use as an indication of brain/
>>>> behavior relationship? The betas should provide the quality/ 
>>>> direction
>>>> of the relationship, but don't say anything about how large or
>>>> important that relationship is. The r squared or also the t or p
>>>> values for each coefficient tell something about the strength of the
>>>> relationship. The issue is, that they give really different activity
>>>> patterns. You can see the topographies of beta values, r squared
>>>> values and p-values in the attached images.
>>>> 
>>>> 2. The second question is which of the single-subject regression
>>>> outputs actually can be used for group level plots and statistics: 
>>>> Is
>>>> it possible to average over e.g. betas or p-vales across subjects, 
>>>> and
>>>> also do group level statistics with (e.g. compare group-level 
>>>> p-values
>>>> or betas between two conditions)?
>>>> 
>>>> Thank you so much in advance!
>>>> 
>>>> Best regards,
>>>> Burcu
>>>> <beta_av_postmean.png><p_values_av_postmean.png><r_squared_av_postmean.png>_______________________________________________
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