I have applied the contrasts that we discussed in the previous mails but they produce doubt results.
In summary, I aim to look at: A- Difference between groups without considerer the covariate effect (I suppose that the maps will be in the intercept folder) ---> ANOVA between 4 groups B- Clusters in which the fMRI (dependent variable) is associated to the structural data (covariate), taking in account the groups (I suppose that the maps will be in the slope folder) ---> MANOVA between 4 groups
Please could you check the contrast reported below? I suspect that there are some errors because, looking at results: The slope map is the inverse in color of the intercept map and the intercept did not correspond to the results which I obtain by using G4V0
C1) gr1-gr2_intercept 1 -1 0 0 0 0 0 0 C2 )gr1-gr2_slope 0 0 0 0 1 -1 0 0 C3) gr1-gr3_intercept 1 0 -1 0 0 0 0 0 C4) gr1-gr3_slope 0 0 0 0 1 0 -1 0 C5) gr1-gr4_intercept 1 0 0 -1 0 0 0 0 C6) gr1-gr4_slope 0 0 0 0 1 0 0 -1 C7) gr2-gr3_intercept 0 1 -1 0 0 0 0 0 C8) gr2-gr3_slope 0 0 0 0 0 1 -1 0 C9) gr2-gr4_intercept 0 1 0 -1 0 0 0 0 C10) gr2-gr4_slope 0 0 0 0 0 1 0 -1 C11) gr3-gr4_intercept 0 0 1 -1 0 0 0 0 C12) gr3-gr4_slope 0 0 0 0 0 0 1 -1 C13) gr1+gr2-vs-gr3+gr4.intercept 0.25 0.25 0.25 0.25 0 0 0 0 C14) gr1+gr2-vs-gr3+gr4.slope 0 0 0 0 0.25 0.25 0.25 0.25 C15) group.effect.intercept 1 -1 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 1 0 0 -1 0 0 0 0 C16) group.effect.slope 0 0 0 0 1 -1 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 1 0 0 -1
Best regards
Stefano
----Messaggio originale---- Da: "Douglas N Greve" greve@nmr.mgh.harvard.edu Data: 11-ott-2017 17.28 A: stdp82@virgilio.it, freesurfer@nmr.mgh.harvard.edu Ogg: Re: [Freesurfer] R: Re: R: Re: R: Re: R: Re: R: Re: R: Re: Map of
covariance
the rational is to make them sum to 1.0 so that the gamma.mgh file has units of mm (or whatever the input units are). It is unimportant for p-values.
On 10/10/2017 01:54 PM, stdp82@virgilio.it wrote:
Thanks
In which contrast I must change "1" with "0.25"? What is the rationale to use 0.25?
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Il 10/10/2017, Douglas N Greve greve@nmr.mgh.harvard.edu ha scritto:
I don't understand what you mean by "where I should use"
I thought I looked through all those contrasts a few weeks ago, no?
On 10/10/2017 04:22 AM, stdp82@virgilio.it wrote:
You have suggested to use 0 0 0 0 .25 .25 .25 .25 to look the map where, considering the group differences, the covariate predicts the dependent variable (functional connectivity) in 4GV1.
Below I'm reporting the contrast that I have used. Please could you check it and suggest correction? Could you explain where I should use 0 0 0 0 .25 .25 .25 .25, please?
Thanks
C1) gr1-gr2_intercept 1 -1 0 0 0 0 0 0 C2 )gr1-gr2_slope 0 0 0 0 1 -1 0 0 C3) gr1-gr3_intercept 1 0 -1 0 0 0 0 0 C4) gr1-gr3_slope 0 0 0 0 1 0 -1 0 C5) gr1-gr4_intercept 1 0 0 -1 0 0 0 0 C6) gr1-gr4_slope 0 0 0 0 1 0 0 -1 C7) gr2-gr3_intercept 0 1 -1 0 0 0 0 0 C8) gr2-gr3_slope 0 0 0 0 0 1 -1 0 C9) gr2-gr4_intercept 0 1 0 -1 0 0 0 0 C10) gr2-gr4_slope 0 0 0 0 0 1 0 -1 C11) gr3-gr4_intercept 0 0 1 -1 0 0 0 0 C12) gr3-gr4_slope 0 0 0 0 0 0 1 -1 C13) gr1+gr2-vs-gr3+gr4.intercept 0.5 0.5 -0.5 -0.5 0 0 0 0 C14) gr1+gr2-vs-gr3+gr4.slope 0 0 0 0 0.5 0.5 -0.5 -0.5 C15) group.effect.intercept 1 -1 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 1 0 0 -1 0 0 0 0 C16) group.effect.slope
0 0 0 0 1 -1 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 1 0 0 -1
On 10/6/17 9:24 AM, stdp82@virgilio.it wrote:
Thank you very much. Where I should put 0 0 0 0 .25 .25 .25 .25? Which are the contrast reported below that I should modify?
C1) gr1-gr2_intercept 1 -1 0 0 0 0 0 0 C2 )gr1-gr2_slope 0 0 0 0 1 -1 0 0 C3) gr1-gr3_intercept 1 0 -1 0 0 0 0 0 C4) gr1-gr3_slope 0 0 0 0 1 0 -1 0 C5) gr1-gr4_intercept 1 0 0 -1 0 0 0 0 C6) gr1-gr4_slope 0 0 0 0 1 0 0 -1 C7) gr2-gr3_intercept 0 1 -1 0 0 0 0 0 C8) gr2-gr3_slope 0 0 0 0 0 1 -1 0 C9) gr2-gr4_intercept 0 1 0 -1 0 0 0 0 C10) gr2-gr4_slope 0 0 0 0 0 1 0 -1 C11) gr3-gr4_intercept 0 0 1 -1 0 0 0 0 C12) gr3-gr4_slope 0 0 0 0 0 0 1 -1 C13) gr1+gr2-vs-gr3+gr4.intercept 0.5 0.5 -0.5 -0.5 0 0 0 0 C14) gr1+gr2-vs-gr3+gr4.slope 0 0 0 0 0.5 0.5 -0.5 -0.5 C15) group.effect.intercept 1 -1 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 1 0 0 -1 0 0 0 0 C16) group.effect.slope 0 0 0 0 1 -1 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 1 0 0 -1 ----Messaggio originale---- Da: "Douglas Greve" greve@nmr.mgh.harvard.edu Data: 9-ott-2017 22.56 A: freesurfer@nmr.mgh.harvard.edu Ogg: Re: [Freesurfer] R: Re: R: Re: R: Re: R: Re: Map of covariance
I don't know what you are asking
On 10/6/17 9:24 AM, stdp82@virgilio.it wrote:
Thank you very much. Where I should put 0 0 0 0 .25 .25 .25 .25? Which are the contrast reported below that I should modify?
C1) gr1-gr2_intercept 1 -1 0 0 0 0 0 0 C2 )gr1-gr2_slope 0 0 0 0 1 -1 0 0 C3) gr1-gr3_intercept 1 0 -1 0 0 0 0 0 C4) gr1-gr3_slope 0 0 0 0 1 0 -1 0 C5) gr1-gr4_intercept 1 0 0 -1 0 0 0 0 C6) gr1-gr4_slope 0 0 0 0 1 0 0 -1 C7) gr2-gr3_intercept 0 1 -1 0 0 0 0 0 C8) gr2-gr3_slope 0 0 0 0 0 1 -1 0 C9) gr2-gr4_intercept 0 1 0 -1 0 0 0 0 C10) gr2-gr4_slope 0 0 0 0 0 1 0 -1 C11) gr3-gr4_intercept 0 0 1 -1 0 0 0 0 C12) gr3-gr4_slope 0 0 0 0 0 0 1 -1 C13) gr1+gr2-vs-gr3+gr4.intercept 0.5 0.5 -0.5 -0.5 0 0 0 0 C14) gr1+gr2-vs-gr3+gr4.slope 0 0 0 0 0.5 0.5 -0.5 -0.5 C15) group.effect.intercept 1 -1 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 1 0 0 -1 0 0 0 0 C16) group.effect.slope 0 0 0 0 1 -1 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 1 0 0 -1
----Messaggio originale---- Da: "Douglas Greve" greve@nmr.mgh.harvard.edu Data: 3-ott-2017 16.19 A: freesurfer@nmr.mgh.harvard.edu Ogg: Re: [Freesurfer] R: Re: R: Re: R: Re: Map of covariance
probably you want 0 0 0 0 .25 .25 .25 .25
On 10/3/17 10:10 AM, stdp82@virgilio.it wrote: > Many thank for your response. > Claryfing my question on point 3, > When I look in group.effect.slope, the map show the group difference
removing
> the effect of the covariate. > Conversely, I would to obtain the map reporting only the effect of
covariate
> on dependent variable (functional connectivity). > Is possible to look on it? > Regards > Stefano > > >> ----Messaggio originale---- >> Da: "Douglas N Greve" greve@nmr.mgh.harvard.edu >> Data: 2-ott-2017 16.58 >> A: freesurfer@nmr.mgh.harvard.edu >> Ogg: Re: [Freesurfer] R: Re: R: Re: Map of covariance >> >> >> >> On 10/01/2017 05:08 PM, stdp82@virgilio.it wrote: >>> Hi, >>> on 4 groups, 1 covariate (4GV1) >>> >>> I run mri_glmfit using the following .mtx >>> >>> C1) gr1-gr2_intercept 1 -1 0 0 0 0 0 0 >>> C2 )gr1-gr2_slope 0 0 0 0 1 -1 0 0 >>> C3) gr1-gr3_intercept 1 0 -1 0 0 0 0 0 >>> C4) gr1-gr3_slope 0 0 0 0 1 0 -1 0 >>> C5) gr1-gr4_intercept 1 0 0 -1 0 0 0 0 >>> C6) gr1-gr4_slope 0 0 0 0 1 0 -1 0 >> should be >> >> 0 0 0 0 1 0 0 -1 >> >>> C7) gr2-gr3_intercept 0 1 -1 0 0 0 0 0 >>> C8) gr2-gr3_slope 0 0 0 0 0 1 -1 0 >>> C9) gr2-gr4_intercept 0 1 0 -1 0 0 0 0 >>> C10) gr2-gr4_slope 0 0 0 0 0 1 0 -1 >>> C11) gr3-gr4_intercept 0 0 1 -1 0 0 0 0 >>> C12) gr3-gr4_slope 0 0 0 0 0 0 1 -1 >>> C13) gr1+gr2-vs-gr3+gr4.intercept 0.5 0.5 -0.5 -0.5 0 0 0 0 >>> C14) gr1+gr2-vs-gr3+gr4.slope 0 0 0 0 0.5 0.5 -0.5 -0.5 >>> C15) group.effect.intercept >>> 1 -1 0 0 0 0 0 0 >>> 1 0 -1 0 0 0 0 0 >>> 1 0 0 -1 0 0 0 0 >>> C16) group.effect.slope >>> 0 0 0 0 1 -1 0 0 >>> 0 0 0 0 1 0 -1 0 >>> 0 0 0 0 1 0 0 -1 >>> >>> Please: >>> 1) Could you check whether the all .mtx are complete and corrected,
in
>>> particular the gr1+gr2-vs-gr3+gr4.intercept and the gr1+gr2-vs-
gr3+gr4.
> slope? >> they look correct, except for the one i noted >>> 2) Could you explain the meaning of: >>> gr1+gr2-vs-gr3+gr4.slope - does the average slope of grp1 and grp2
differ
> from that of grp3 and 4 >>> gr1+gr2-vs-gr3+gr4.intercept - same >>> group.effect.slope - interaction between group and covariate >>> group.effect.intercept - is there an effect of group on the inercept >>> 3) Which is the contrast identifying the effect of covariate on
group
>>> differences? >> not sure what you mean >>> Thanks >>> >>> Best regards >>> >>> >>> Stefano >>> >>> >>> >>>> ----Messaggio originale---- >>>> Da: "Douglas N Greve" greve@nmr.mgh.harvard.edu >>>> Data: 5-set-2017 22.59 >>>> A: freesurfer@nmr.mgh.harvard.edu >>>> Ogg: Re: [Freesurfer] R: Re: Map of covariance >>>> >>>> you would need to create a contrast to look for the interaction. If
you
>>>> have four gruops and 1 covariate, then it would be >>>> >>>> 0 0 0 0 1 -1 0 0 >>>> >>>> 0 0 0 0 1 0 -1 0 >>>> >>>> 0 0 0 0 1 0 0 -1 >>>> >>>> >>>> >>>> On 09/05/2017 04:32 PM, stdp82@virgilio.it wrote: >>>>> Hi, >>>>> e.g., by considering two or more groups, I would like to map the
clusters
>>>>> reporting the covariance between the functional connectivity or
cortical
>>>>> thickness (dependent variable) and age, tacking in account the
group
>>>>> differences. >>>>> Instead, I'm not interested to map the group differences, taking
in
> account >>>>> the nuisance factors. >>>>> Thanks, >>>>> Stefano >>>>> >>>>>> ----Messaggio originale---- >>>>>> Da: "Douglas N Greve" greve@nmr.mgh.harvard.edu >>>>>> Data: 5-set-2017 18.12 >>>>>> A: freesurfer@nmr.mgh.harvard.edu >>>>>> Ogg: Re: [Freesurfer] Map of covariance >>>>>> >>>>>> I don't understand what you are asking. can you elaborate? >>>>>> >>>>>> >>>>>> On 08/30/2017 12:50 PM, stdp82@virgilio.it wrote: >>>>>>> Hi list, >>>>>>> by applying a design e.g. 4GV1 in fsgd I could assess the
dependence
>>>>>>> of group differences taking in account the effect of covariate. >>>>>>> Anyway, where I should look if I want assess the the map showing
the
>>>>>>> clusters in which the dependent variable is associated to
covariate,
>>>>>>> tacking in account the group difference? Please could you
suggest
my
>>>>>>> the path? >>>>>>> Thanks >>>>>>> >>>>>>> Stefano >>>>>>> >>>>>>> >>>>>>> _______________________________________________ >>>>>>> Freesurfer mailing list >>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>> -- >>>>>> Douglas N. Greve, Ph.D. >>>>>> MGH-NMR Center >>>>>> greve@nmr.mgh.harvard.edu >>>>>> Phone Number: 617-724-2358 >>>>>> Fax: 617-726-7422 >>>>>> >>>>>> Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting >>>>>> FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 >>>>>> www.nmr.mgh.harvard.edu/facility/filedrop/index.html >>>>>> Outgoing: ftp://surfer.nmr.mgh.harvard.
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