Thank you, Anderson.

Regards.

VM

On Thu, Feb 2, 2017 at 11:06 PM, Anderson M. Winkler <wink...@fmrib.ox.ac.uk
> wrote:

> Hi VM,
>
> They can stay all in the same .csv file. The "fwep" files will have
> p-values corrected across all columns of this input.
>
> All the best,
>
> Anderson
>
>
> On 2 February 2017 at 12:09, neuroimage analyst <
> neuroimage.anal...@gmail.com> wrote:
>
>> Thanks, Anderson. If there are several other measures such as volume,
>> thickness, FA,  can I then put them in a single csv file and run the
>> command or I have to create 3 csv files, one each for volume, thickness,and
>> FA and also invoke -corrmod?
>>
>> Thanks
>>
>> Regards
>> VM
>>
>> On Feb 2, 2017 1:01 AM, "Anderson M. Winkler" <wink...@fmrib.ox.ac.uk>
>> wrote:
>>
>> Hi VM,
>>
>> Please see below:
>>
>>
>> On 1 February 2017 at 02:38, neuroimage analyst <
>> neuroimage.anal...@gmail.com> wrote:
>>
>>> Hi,
>>>
>>> We extracted volume measures from 7 ROIs in 2 groups and compared
>>> a) Mean of each ROI volume between group, and compared independently
>>> such as
>>> i) whether mean of ROI 1 in group 1 is equal to mean of ROI1 in group 2
>>> ii)whether mean of ROI 2 in group 1 is equal to mean of ROI2 in group 2
>>>  and so on
>>>
>>
>> This means 7 comparisons, or 14 if you test both directions (tails)
>> separately.
>>
>>
>>>
>>> b) Plotted the mean ROI volume for 2 independent measures and compared
>>> whether the slope between and within group is significantly different. such
>>> as
>>> i) Slope of ROI1 is positively associated with MoCA , age (grp1) ?
>>> ii) Slope of ROI1 is negatively associated with MoCA, age (grp2) ?
>>> iii) Slope of ROI1 vs MoCA (grp1) is significantly different
>>> than slope of ROI1 vs MoCA (grp2) ?
>>> iv) Slope of ROI1 vs MoCA (grp2) is significantly different
>>> than slope of ROI2 vs MoCA (grp2) ?
>>>
>>
>> These sound tests for main effects and interaction, with various
>> combinations possible.
>>
>>
>>>
>>> Q1) Do we have to perform multiple comparisons for (a) and (b)?
>>>
>>
>> Yes.
>>
>>
>>
>>> Q2) If yes, do we correct across 7 measurements for (a) and 2
>>> measurements for (b) or 7 measurements for both (a) and (b)?
>>>
>>
>> You could put the values for the 7 ROIs in a table in .csv format, with
>> one column per ROI and one row per subject. This would be the input data.
>> Create a design matrix as:
>>
>> EV1: 0 or 1 coding for group 1
>> EV2: 0 or 1 coding for group 2
>> EV3: MoCA group 1
>> EV4: MoCA group 2
>> EV5: Age group 1
>> EV6: Age group 2
>> etc
>>
>> Then define a set of contrasts such as:
>>
>> C1: [1 -1 0 0 0 0 ...] - This tests if mean for group 1 > mean for group 2
>> C2: [-1 1 0 0 0 0 ...] - This tests if mean for group 1 < mean for group 2
>> C3: [0 0 1 -1 0 0 ...] - This tests if the slope for MoCA for group 1 >
>> slope for MoCA for group 2
>> C4: [0 0 -1 1 0 0 ...] - This tests if the slope for MoCA for group 1 <
>> slope for MoCA for group 2
>> C5: [0 0 1 0 0 0 ...] - This tests if slope for MoCA for group 1 > 0
>> C6: [0 0 -1 0 0 0 ...] - This tests if slope for MoCA for group 1 < 0
>> etc
>>
>> You'd run this analysis in PALM with something as:
>>
>> *palm -i input.csv -d design.mat -t design.con -corrcon -o myresults
>> -logp*
>>
>>
>> Hope this helps!
>>
>> All the best,
>>
>> Anderson
>>
>>
>>
>>> There is evidence to both performing and nonperforming multiple
>>> comparisons In the literature.
>>>
>>> Any response (hopefully pointing to a literature) will be greatly
>>> appreciated.
>>>
>>> Thanks
>>>
>>> Regards
>>>
>>> --VM
>>>
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