[Mne_analysis] Grand mean across subjects

[Emanuela Liaci]

Hi,

thanks for your response. So I tried what you suggested me, by creating a
list of evokeds (here printed the list for one condition and just 2
subjects: [<Evoked  |  comment : 'Unknown', kind : average, time :
[-0.060000, 0.798000], n_epochs : 48, n_channels x n_times : 32 x 430, ~177
kB>, <Evoked  |  comment : 'Unknown', kind : average, time : [-0.060000,
0.798000], n_epochs : 50, n_channels x n_times : 32 x 430, ~177 kB>]).

When I do: sem_data = sem(np.stack([x.data for x in evokeds], axis=2),
axis=2), I get this error: AttributeError: 'module' object has no attribute
'stack'

What does this mean?

Thanks again,
Emanuela



On Thu, Aug 25, 2016 at 9:16 AM, Mikołaj Magnuski <mmagnuski at swps.edu.pl>
wrote:

> Let’s say you have a list of evokeds - evokeds. To get SEM you can do the
> following:
>
> import numpy as npfrom scipy.stats import sem
>
> sem_data = sem(np.stack([x.data for x in evokeds], axis=2), axis=2)
>
> Now sem_data is an array of size (n_channels, n_samples). To get the
> lower bound of the SEM you would have to subtract sem_data form the data
> of your grand average and add it to get the upper bound.
> ​
>
> 2016-08-24 12:23 GMT+02:00 Emanuela Liaci <emanuela.liaci at gmail.com>:
>
>> Thanks for the response. A question remains: how can I get the standard
>> error of the mean?
>>
>> Greetings
>> Emanuela
>>
>> On Wed, Aug 17, 2016 at 9:25 PM, Alexandre Gramfort <
>> alexandre.gramfort at telecom-paristech.fr> wrote:
>>
>>> hi,
>>>
>>> http://martinos.org/mne/dev/generated/mne.grand_average.html
>>>
>>> HTH
>>> Alex
>>>
>>> On Tue, Aug 16, 2016 at 11:41 AM, Emanuela Liaci
>>> <emanuela.liaci at gmail.com> wrote:
>>> > Hi,
>>> >
>>> > I would like to calculate the grand mean and the standard error across
>>> > subjects for each of my conditions. Is there a specific function in
>>> mne to
>>> > do it starting from each subject's EvokedArray ?
>>> >
>>> > Many thanks
>>> > Emanuela
>>> >
>>> >
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