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

Maria Hakonen maria.hakonen at gmail.com
Sun Dec 21 10:35:45 EST 2014
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Hi Denis,

I tried that and got  the following p values: 0.02993846,  0.47414992
The corresponding Greenhouse-Geisser corrected values computed with
Statistica were: 0.026775, 0.462423.
Huynh-Feldt correction gives 0.023894, 0.473539 and lower-bound correction
0.036458, 0.427778

The uncorrected values calculated with Statistica and Python are equal but
also the corrected values are almost equal. So, maybe f_twoway_rm works
correctly now?

It would also be interesting to do post-hoc comparisons between conditions
but I think that Python doesn't have function for post-hoc test, or at
least I didn't found it?

-Maria

2014-12-21 16:49 GMT+02:00 Denis-Alexander Engemann <
denis.engemann at gmail.com>:

> Should be Greenhouse-Geisser,
> also see source code:
>
>
> https://github.com/mne-tools/mne-python/blob/master/mne/stats/parametric.py#L249
>
> 2014-12-21 15:47 GMT+01:00 Denis-Alexander Engemann <
> denis.engemann at gmail.com>:
>
>> [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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