[Eeglablist] comparing normal and clinical populations

[Arnaud Delorme]

Dear Jose,

using 1000 trials, you may perform inferential testing on your subject's trial population. For instance, you H0 null hypothesis may be "There is no difference between the trial activity between condition A and condition B in subject X". If you reject the null hypothesis, then you may conclude that there is a significant difference between A and B for subject X. In other words, you make an inference about the trial population of subject X. If you were to record additional trials of conditions A and B in subject X, you should be able to reproduce your significant effect (subject to the p-value uncertainty obviously).

Now, if you have several subjects, you may perform inferential testing on the subjects' population (i.e. the general population assuming your subject sample is appropriate). Your H0 null hypothesis may be "There is no difference between the trial activity between condition A and condition B in the general population". If you record additional subjects (not necessarily the same ones), you should be able to reproduce your effect.

To combine the two (subjects and trials) means that you need to change the null hypothesis. Now, your H0 null hypothesis may be "There is no difference between the trial activity between condition A and condition B in subject X, Y, and Z". Your are making an inference about the trial population of subject X, Y, and Z. If you reject this null hypothesis, you should be able to record more data for subject X, Y, and Z and reproduce the effect. 

The last approach is valid (and possible in EEGLAB) but less interesting than the one using one value per subject - because you usually want to make inference about the general population, not about a few subjects.

This is my take on it but I am not a statistician, so there might be different approaches/interpretations.
Best,

Arno

On Dec 4, 2011, at 11:02 AM, Jose Rebola wrote:

> Hi
> 
> I am running a study to investigate differences between  williams syndrome patients and controls in a visual task. I have eight subjects of each population.
> 
> How do I compare the amplitude of the P100 between the populations?
> 
> Should i include only one value (the peak around 100ms on each of the subject's average) per subject ? 
> It seems to me that if i do this i will only have one value per subject and i am "throwing away" the 100 trials per condition that i have
> 
> Isn't there a way that i can compare between populations while retaining within-subject variability?
> Otherwise, how does it compensate to perform 1000 trials instead of 10?
> 
> I only know how to do two-level analysis when all subjects perform two conditions for example, thus getting one value of "effect" per subject and moving to the next level...
> 
> Isn't there any paralle of this to two populations?
> 
> Hope somebody can help me,
> 
> José Rebola
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