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Hi Rujing, Yep, use -1 for the negative. For contrasts as these, in which just one parameter (beta) is being tested, the sign of the contrast is the sign of the side that you are testing. All the best, Anderson On 14/01/2014 13:23, charujing123 wrote: > Hi Anderson, > Thanks very much Anderson. > What an idiot I am! > I see. As I put the number "1" in the contrast, so the significant > result will be the positive not the neagtive. If I want to get the > negtive correlation, I should put the "-1" in the proper site in the > contrast. > Am I right? > All the best. > Rujing Zha > University of Science and Technology of China > [log in to unmask] <mailto:[log in to unmask]> > [log in to unmask] <mailto:[log in to unmask]> > [log in to unmask] <mailto:[log in to unmask]> > 2014-01-14 > ------------------------------------------------------------------------ > charujing123 > ------------------------------------------------------------------------ > *发件人：*"Anderson M. Winkler" <[log in to unmask]> > *发送时间：*2014-01-14 20:09 > *主题：*Re: [FSL] glm_output by randomise > *收件人：*"FSL"<[log in to unmask]> > *抄送：* > Hi Rujing, > > You don't need to open the beta images to see what is the sign. With > the contrasts you are showing, any significant result has a positive > regression coefficient. If you wanted to test the negative side, you'd > use contrasts with -1 instead of 1. > > If, however, you had to open the images with the betas, yes, it would > be the 5th volume. > > All the best, > > Anderson > > > On 14/01/2014 06:36, charujing123 wrote: >> Hi Anderson and other FSL experts, >> Here is my design matrix, contrast and design.fsf in the attachment. >> In my case, I completed the correlation. In the design.mat, there are >> 5 regressors:sex,age,edu,score_week, and score_year(ordered from left >> to right).Also I have 5 contrasts,and I found the second >> contrast(i.e. score_year) has a corrected significant result, so I >> want to know whether the coefficient of correlation is negtive or >> positive. So I run randomise --glm_output option, and it generates 5 >> stats images(i.e. >> *_glm_pe_tstat1,*_glm_pe_tstat2,*_glm_pe_tstat3,*_glm_pe_tstat4,*_glm_pe_tstat5). >> Now I want to know which volume in *_glm_pe_tstat2 I can get the >> positive or negtive beta value? Maybe the 5th volume in >> *_glm_pe_tstat2, as the score_year is the 5th regressor in design.mat? >> Thanks. >> All the best. >> Rujing Zha >> 2014-01-14 >> ------------------------------------------------------------------------ >> charujing123 >> ------------------------------------------------------------------------ >> *发件人：*"Anderson M. Winkler" <[log in to unmask]> >> *发送时间：*2013-12-14 00:10 >> *主题：*Re: [FSL] glm_output by randomise >> *收件人：*"FSL"<[log in to unmask]> >> *抄送：* >> Hi Rujing, >> >> Say you have a contrast C = [1 -1 0]', and for a certain voxel, you >> have beta = [1 4 2]'. The COPE is simply C'*beta = [1 -1 0] * [1 4 2] >> = 1*1 -1*4 + 0*2 = -3. This is what goes in the numerator of the t >> statistic. >> >> A suggestion of a book to begin studying is >> http://www.amazon.co.uk/Handbook-Functional-MRI-Data-Analysis/dp/0521517664 >> >> All the best, >> >> Anderson >> >> >> >> >> On 13 December 2013 15:53, Rujing Zha <[log in to unmask] >> <mailto:[log in to unmask]>> wrote: >> >> Hi Anderson, >> Thanks for your precious help. >> I knew the *pe* is what I need to get the beta of regressors. >> Most of those you told me I can understand except the *cope*. >> Would you please introduce me a website or manu describing the >> "contrasts of parameter estimates" detaily? >> Thanks in advance. >> All the best. >> 2013-12-13 >> ------------------------------------------------------------------------ >> /Rujing Zha/ >> ------------------------------------------------------------------------ >> *发件人：*"Anderson M. Winkler" <[log in to unmask] >> <mailto:[log in to unmask]>> >> *发送时间：*2013-12-13 19 <tel:2013-12-13%C2%A019>:18 >> *主题：*Re: [FSL] glm_output by randomise >> *收件人：*"FSL"<[log in to unmask] <mailto:[log in to unmask]>> >> *抄送：* >> Hi Rujing, >> >> Please, see below: >> >> On 13 December 2013 02:42, Rujing Zha <[log in to unmask] >> <mailto:[log in to unmask]>> wrote: >> >> Dear all, >> I just type "randomise -i GM -o test -m GM_mask -d design.mat >> -t design.con -n 5000 -T -D --glm_output=GLM_test", but it >> just generate test_glm_cope_tstat*, test_glm_pe_tstat*, >> test_glm_sigmasqr_tstat*, test_glm_varcope_tstat* for >> glm_output. >> I have two questions about this: >> first: Did GLM_test cannot be used to name the glm output by >> "--glm_output=GLM_test" or just type "--glm_output" not >> "--glm_output=GLM_test"? >> >> >> Use just --glm_output. The output filenames will be prefixed by >> the string you gave with the option -o (in this case "test"), >> plus "glm", to indicate that these refer to GLM terms. >> >> second: What are meaning of *cope*, *pe*, *sigmasqr*, *varcope*? >> >> >> These are all the 4 outputs of the --glm_output, and I suspect >> that if you aren't sure they mean, you probably don't need them. >> In any case: >> >> - The *pe* are the parameter estimates, also known as betas (this >> image has as many volumes as regressors in the design); >> - The *cope* are the contrasts of parameter estimates, one image >> per contrast. It's the inner product between the contrast vector >> and the betas; >> - Because the *pe* are estimates, so are the *cope*. These >> estimates have an uncertainty surrounding them, and the variance >> around these estimates is the *varcope*; >> - The *sigmasqr* is the variance of the residuals. >> >> Hope this helps. >> >> All the best, >> >> Anderson >> >> Thanks. >> All the best. >> 2013-12-13 >> ------------------------------------------------------------------------ >> /Rujing Zha/ >> >> >> >