[MINC-users] glim_image
Jamila Ahdidan
minc-users@bic.mni.mcgill.ca
Mon Apr 11 15:59:03 2005
--0-1277789368-1113249529=:59368
Content-Type: text/plain; charset=us-ascii
Dear Jason,
Thanks for your explanation. It help a lot!
I have one (or 2) more question. The results from a glim_image with a matrix an intercept and the one without intercept are the same, except from the range of t values that is bigger without intercept, which allows me to define highly significant areas (even after the very conservative bonferroni correction). So, I wonder whether the results from the glim without intercept can be used to give an estimate of what could be found if we had a bigger sample size. Do you think I can use the results from the glim without intercept in some way? and if yes how?
I hope you'll find the time to answer!
Many regards,
Jamila
Jason Lerch <jason@bic.mni.mcgill.ca> wrote:
Greetings again,
I've attached a graph which shows the difference - the data was
generated using the following function:
y = 2 + 0.5x + Error
where x is a simple sequence between 0 and 10.
There are two regression lines through the graph. The one in blue fits
a model including the intercept term, the one in red fits a model
without an intercept. You can see that the red line takes on a value of
0 when x=0 - and that therefore the fit is not as accurate as the blue
line.
None of this stuff is specific to glim_image - this is all standard
linear model statistics. One of the best online references that I know
about is here:
http://www.itl.nist.gov/div898/handbook/
though there surely are others as well.
Good luck,
Jason
On Apr 10, 2005, at 3:41 AM, Jamila Ahdidan wrote:
> Hi Jason,
> Well I have to say that I don't use glim_image to perform a VBM study,
> but to perform a t test at each voxel to assess the difference between
> my group of patients and my group of controls. So, I don't really know
> whether I want to force to be 0 at x=0. (I don't really know what that
> means!).
> Do you think I'm using the wrong minc command, and if yes do you have
> another idea?
>
> Thanks a lot,
> Jamila
>
> Jason Lerch wrote:
>
> On Apr 9, 2005, at 6:51 PM, Jamila Ahdidan wrote:
>
> > My dilema is whether I should just keep
> > my good results and forget about the intercept in the
> > matrix, or I should stick to the intercept and
> > conclude that nothing is interpretable from my
> > results.
>
> Is there any reason to force the slope to be 0 at x=0? If you have
> standard VBM density data, then that is an invalid assumption, since
> there is every reason to allow the y to take on an arbitrary value at
> x=0, so you would include that column of ones for your intercept term.
> If you have different data then this assumption might be valid -
> something that is the case, for example, when looking at asymmetry VBM.
> But by and large you will want an intercept.
>
> Hope this helps,
>
> Jason
>
> _______________________________________________
> MINC-users@bic.mni.mcgill.ca
> http://www.bic.mni.mcgill.ca/mailman/listinfo/minc-users
>
> Do you Yahoo!?
> Yahoo! Mail - Find what you need with new enhanced search. Learn more.
---------------------------------
Do you Yahoo!?
Yahoo! Small Business - Try our new resources site!
--0-1277789368-1113249529=:59368
Content-Type: text/html; charset=us-ascii
<DIV>
<DIV>Dear Jason,</DIV>
<DIV>Thanks for your explanation. It help a lot!</DIV>
<DIV>I have one (or 2) more question. The results from a glim_image with a matrix an intercept and the one without intercept are the same, except from the range of t values that is bigger without intercept, which allows me to define highly significant areas (even after the very conservative bonferroni correction). So, I wonder whether the results from the glim without intercept can be used to give an estimate of what could be found if we had a bigger sample size. Do you think I can use the results from the glim without intercept in some way? and if yes how?</DIV>
<DIV> </DIV>
<DIV>I hope you'll find the time to answer!</DIV>
<DIV> </DIV>
<DIV>Many regards,</DIV>
<DIV>Jamila<BR><BR><BR><B><I>Jason Lerch <jason@bic.mni.mcgill.ca></I></B> wrote:</DIV>
<BLOCKQUOTE class=replbq style="PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #1010ff 2px solid">Greetings again,<BR><BR>I've attached a graph which shows the difference - the data was <BR>generated using the following function:<BR><BR>y = 2 + 0.5x + Error<BR><BR>where x is a simple sequence between 0 and 10.<BR><BR>There are two regression lines through the graph. The one in blue fits <BR>a model including the intercept term, the one in red fits a model <BR>without an intercept. You can see that the red line takes on a value of <BR>0 when x=0 - and that therefore the fit is not as accurate as the blue <BR>line.<BR><BR>None of this stuff is specific to glim_image - this is all standard <BR>linear model statistics. One of the best online references that I know <BR>about is here:<BR><BR>http://www.itl.nist.gov/div898/handbook/<BR><BR>though there surely are others as well.<BR><BR>Good luck,<BR><BR>Jason<BR><BR><BR><BR>On Apr 10, 2005, at 3:41 AM, Jamila Ahdidan wrote:<BR><BR>>
Hi Jason,<BR>> Well I have to say that I don't use glim_image to perform a VBM study, <BR>> but to perform a t test at each voxel to assess the difference between <BR>> my group of patients and my group of controls. So, I don't really know <BR>> whether I want to force to be 0 at x=0. (I don't really know what that <BR>> means!).<BR>> Do you think I'm using the wrong minc command, and if yes do you have <BR>> another idea?<BR>> <BR>> Thanks a lot,<BR>> Jamila<BR>><BR>> Jason Lerch <JASON@BIC.MNI.MCGILL.CA>wrote:<BR>><BR>> On Apr 9, 2005, at 6:51 PM, Jamila Ahdidan wrote:<BR>><BR>> > My dilema is whether I should just keep<BR>> > my good results and forget about the intercept in the<BR>> > matrix, or I should stick to the intercept and<BR>> > conclude that nothing is interpretable from my<BR>> > results.<BR>><BR>> Is there any reason to force the slope to be 0 at x=0? If you have<BR>> standard
VBM density data, then that is an invalid assumption, since<BR>> there is every reason to allow the y to take on an arbitrary value at<BR>> x=0, so you would include that column of ones for your intercept term.<BR>> If you have different data then this assumption might be valid -<BR>> something that is the case, for example, when looking at asymmetry VBM.<BR>> But by and large you will want an intercept.<BR>><BR>> Hope this helps,<BR>><BR>> Jason<BR>><BR>> _______________________________________________<BR>> MINC-users@bic.mni.mcgill.ca<BR>> http://www.bic.mni.mcgill.ca/mailman/listinfo/minc-users<BR>><BR>> Do you Yahoo!?<BR>> Yahoo! Mail - Find what you need with new enhanced search. Learn more.</BLOCKQUOTE></DIV><p>
<hr size=1>Do you Yahoo!?<br>
Yahoo! Small Business - <a href="http://us.rd.yahoo.com/evt=31637/*http://smallbusiness.yahoo.com/resources/">Try our new resources site!</a>
--0-1277789368-1113249529=:59368--