[Mne_analysis] [Mne analysis] two sample t-test with spatio_temporal_cluster_test

[Denis-Alexander Engemann]

Ahh. For two conditions F should be the abs(T**2). You can just use a
t-test for indpendent samples here instead as statfun.
On Mon, 12 Jun 2017 at 10:13, Talitha Ford <tcford at swin.edu.au> wrote:

> Hi Dennis,
> Thank you, this is the script I’ve been working from. The problem I am
> having though, is that as f-stats are >0, they do not indicate which group
> is larger than the other, which is what I would like to know. I have tried
> to use scipy.stats.ttest_ind but I get this error:
> ValueError: could not broadcast input array from shape (1000) into shape
> (614520)
>
> The command is:
>  T_obs, clusters, cluster_p_values, H0 = clu =\
> spatio_temporal_cluster_test(all_data, connectivity=connectivity,
> n_jobs=2, stat_fun= scipy.stats.ttest_ind)
>
> all_data is 2 lists (2 groups) of 16 and 19 participants, with 30 time
> points of 20484 vertices for each participant.
>
> I hope that makes sense (and there is a possible work around!). Thanks
> again for you help,
>
> Talitha
>
>
> On 12 Jun 2017, at 05:33, Denis-Alexander Engemann <
> denis.engemann at gmail.com> wrote:
>
> Hi Talitha,
>
> you can run the permutation clustering with a wide array of contrasts.
> This might be what you are looking for:
>
>
> http://martinos.org/mne/dev/auto_tutorials/plot_stats_cluster_spatio_temporal_2samp.html
>
> I hope this helps,
> Denis
>
> On Sun, Jun 11, 2017 at 12:00 PM Talitha Ford <tcford at swin.edu.au> wrote:
>
>> Dear all,
>>
>> Similar to conducing a pair samples t-test on source data using
>> spatio-temporal clustering, allowing the visualisation of clusters where
>> condition A > condition B and vice versa, is it possible to run an
>> independent samples t-test to visualise differences between two groups? The
>> 2 samples permutation tests currently available are limited in that they
>> plot F statistics that don’t give a direction of the difference between the
>> groups. Basically, is it possible to identify clusters that differ
>> significantly between the groups, as well as identify/visualise the
>> direction in which they differ?
>>
>> I am currently attempting to extract the cluster values for each
>> participant to get an overall mean for each vertex within the cluster to
>> compare between groups, but this seems very inefficient.
>>
>> Cheers,
>> Talitha
>>
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