[Mne_analysis] temporal decoding: group analysis for mixed design

[Andrew R. Dykstra]

Hi JR,

Is there a reference for that? i.e., that non-parametric stats aren't
subject to the same inferential issue as t-tests?

Thanks, Andy

On Tue, Dec 19, 2017 at 12:12 PM JR KING <jeanremi.king at gmail.com> wrote:

> While this paper raises an important subtlety (a significant t-test over
> subjects' decoding accuracies indicates that there "are some people in the
> population whose fMRI data carry information about the experimental
> condition — but" [...] not that there is "an effect that is typical in the
> population"), my understanding is that this particular issue is not a
> problem for non-parametric statistics.
>
> On 19 December 2017 at 11:15, Alday, Phillip <Phillip.Alday at mpi.nl> wrote:
>
>> Do be careful when doing group-level statistics via inferential
>> statistics on accuracy scores -- Allefeld at al 2016 show some of the
>> problems with the naive approach using things like t-tests or ANOVA. You
>> could use a Binomial/Bernoulli regression model to get around some of
>> points they raise without needing to use their minimum information
>> statistic.
>>
>> Best,
>>
>> Phillip
>>
>> On 18/12/17 11:24, JR KING wrote:
>>
>> Dear Yi-hui
>>
>> Decoding is generally not really adapted for mix-designed, as the models
>> are traditionally fit at the single subject level - i.e. your model cannot
>> be easily optimized to look for an across-subject effect.
>>
>> You can however compare the decoding scores across subjects/conditions as
>> a first approximation, and specify individual subjects' score as your
>> random variable.
>>
>> For multifactorial within-subject effects, a simple approach can be to
>> implement RSA; we recently added this example in MNE:
>>
>> https://mne-tools.github.io/stable/auto_examples/decoding/decoding_rsa.html
>>
>> I will refer you to Kriegoskorte's RSA papers to see how you adapt this
>> analysis to your specific needs,
>>
>> Kindest regards,
>>
>> Jean-Rémi
>>
>> On 18 December 2017 at 02:05, Yi-hui Hung <vedahung1116 at gmail.com> wrote:
>>
>>> Hello MNE experts,
>>>
>>> I have MEG data with two within-subject factors (each having 2 and 3
>>> levels) and one between-subject factor (2 levels).  I performed
>>> decoding analysis on my MEG data by using the function " time_decod.fit".
>>> The question is how to perform group analysis in subject's decoding data in
>>> MNE (or outside MNE) for my mixed design (2 x 3 x 2 factorial design).
>>> Besides, I have another dependent variable by using "predict_proba"
>>> function to get the predicting probability. I want to test whether the
>>> distribution of predicting probability differ according to my design.
>>> Whether the difference of the distribution continues in time (e.g.,
>>> 200-300ms after stimulus onset) does not matter. Suggestions will be
>>> appreciated.
>>>
>>>
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>>
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-- 
Andrew R. Dykstra, PhD
Department of Neurology
Ruprecht-Karls-Universität Heidelberg
andrew.dykstra at med.uni-heidelberg.de
Europe: +49.157.7028.2162, North America: +1.786.263.9742
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