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.
edu/transfer/outgoing/flat/greve/
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>
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