[Mne_analysis] Comparison of brain responses under three different conditions?

Sun Dec 21 09:47:49 EST 2014

[f,p]=f_twoway_rm(data,factor_levels=[2,3], correction=True)


2014-12-21 15:45 GMT+01:00 Maria Hakonen <maria.hakonen at gmail.com>:

> Hi Denis,
>
> Are you sure that the sphericity correction is implemented by f_twoway_rm?
> I tested it with data where the assumption of sphericity is violated. I
> calculated p values with Statistica and corrected them using the
> lower-bound estimate, Greenhouse-Geisser correction and the Huynh-Feldt
> correction. However, the p-values given by f_twoway_rm were equal with the
> uncorrected values I calculated with Statistica. I used f_twoway_rm as:
>
> [f,p]=f_twoway_rm(data,factor_levels=[2,3])
>
> where data is hemisphere*sesion ANOVA table.
>
> -Maria
>
> 2014-12-21 15:08 GMT+02:00 Denis-Alexander Engemann <
> denis.engemann at gmail.com>:
>
>>
>>
>> 2014-12-21 14:00 GMT+01:00 Maria Hakonen <maria.hakonen at gmail.com>:
>>
>>> Hi,
>>>
>>> Is it that when I have hemisphere*session ANOVAs, I can use f_twoway_rm,
>>> and this gives the corrected values?
>>>
>>
>> with correction=True
>>
>>
>>> Should one-way ANOVA be used in the cases where I am not interested in
>>> hemisperic asymmetry? Is there any function for one way ANOVA that gives
>>> sphericity corrected values?
>>>
>>>
>> A one-way ANOVA is currently not implemented. But you can just look at
>> the relevant main effect. Should be equivalent.
>>
>>
>>> -Maria
>>>
>>> 2014-12-21 14:21 GMT+02:00 Denis A. Engemann <denis.engemann at gmail.com>:
>>>
>>>> Hi Maria,
>>>>
>>>> On 21 Dec 2014, at 12:51, Maria Hakonen <maria.hakonen at gmail.com>
>>>> wrote:
>>>>
>>>> Hi Denis,
>>>>
>>>> Should I use two-way ANOVA if I also want to compare hemispheres, i.e.
>>>> have a 2*3 (hemisphere*session) ANOVA table?
>>>>
>>>>
>>>> Sounds like the repeated measures anova is what you want to do here
>>>> indeed. I just realized the sphericity correction is actually implemented
>>>> by our code. So that should fly. Checkout the correction parameter.
>>>>
>>>>
>>>> I would need to do group level analysis.
>>>>
>>>> -Maria
>>>>
>>>>
>>>> 2014-12-21 12:38 GMT+02:00 Denis-Alexander Engemann <
>>>> denis.engemann at gmail.com>:
>>>>
>>>>> Hi Maria,
>>>>>
>>>>> 2014-12-21 10:18 GMT+01:00 Maria Hakonen <maria.hakonen at gmail.com>:
>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> I would need to find the time intervals where there are statistically
>>>>>> significant differences between MEG responses measured under three
>>>>>> different conditions.  I study the responses by comparing the mean values
>>>>>> in steps of 200 ms between the range of 400-2400 ms. I would like to do
>>>>>> this for responses from several brain areas. What could be the best way to
>>>>>> compare the mean values of the tree responses?
>>>>>>
>>>>>>
>>>>> Single subject or group level?
>>>>> For single subject a standard F-test would be appropriate. For groups
>>>>> a oneway repeated measures ANOVA, if I understand your design correctly
>>>>> (simply 3 different conditions).
>>>>>
>>>>>
>>>>>> I have planned to try f_twoway_rm in a loop. However, when rmANOVA is
>>>>>> used, sphericity test is needed, and if the assumption of sphericity is
>>>>>> violated, p values need to be corrected. Is there any function for this in
>>>>>> Python (e.g. Mauchly's sphericity test and Greenhouse-Geisser test)?
>>>>>>
>>>>>>
>>>>> Note that this only needed if you have more than 2 factors with more
>>>>> than two levels. Currently this is not implemented in our stats code. The
>>>>> other questions is why you need a 2-way test for 3 conditions. I probably
>>>>> did not fully understand your design.
>>>>>
>>>>> Denis
>>>>>
>>>>>
>>>>>> Many thanks already in advance!
>>>>>>
>>>>>> Regards,
>>>>>> Maria
>>>>>>
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