Hi Anderson, Thanks Anderson,I see. For the 1st question,did I need demean behavior data when I used -D option? For the 2nd question,what I think below are appropriate? 1,Output of randomise is an inference based on non-paramatric method, and result from FEAT is an inference based on paramatric method. 2,For VBM and TBSS(for gray matter and white matter respectively),can I use the same GLM setup which is used for randomise previously to perform paramatric inference by FEAT at the end(not by randomise)? That is to say, I want to use FEAT not randomise to perform paramatric inference. Thanks again, Anderson. All the best. Rujing Zha 2014-02-07 charujing123 发件人:Mark Jenkinson <[log in to unmask]> 发送时间:2014-02-07 17:45 主题:Re: [FSL] question about "randomise -D option" and "GLM design in Two-Group Difference" 收件人:"FSL"<[log in to unmask]> 抄送: Hi, The -D option in recent versions of FSL removes the mean from both the data and the design matrix EVs. Permutations and t-tests are not mutually exclusive. You are still using t-tests (or F-tests if you combine t-tests) in randomise, but the method by which it performs inference (calculating probabilities) uses a permutation-based non-parameteric method, as opposed to tools like FEAT where parametric methods are used. This is totally separate from the fact that you are performing a t-test. All the best, Mark On 7 Feb 2014, at 03:12, charujing123 <[log in to unmask]> wrote: Hi Anderson and other FSL experts, I have a two questions about FSL statistics. 1,As we know, there is a -D option in randomise,which is "demeaning data temporally before model fitting". What I wonder is -D option demean what data, either only MR data or both for MR data and behavior data? 2,http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#Two-Group_Difference_.28Two-Sample_Unpaired_T-Test.29 In method of this website, I can do two-sample unpaired t-test. In "randomsie details", I see word "permutations". So I didnot know whether it is a unpaired t-test or a permutaion test.There is same question in "Two-Group Difference Adjusted for Covariate". If they are all t-test, I want to know the functions of permutations and how to do permutation test. Thanks Anderson and others. All the best. Rujing Zha 2014-02-07 charujing123