How sure are you that you are using the exact same model? Can you output the design matrix from SPSS? Can you input the FS design matrix into SPSS? Are you sure you are using the exact same input data?
On 02/04/2015 06:32 PM, Bronwyn Overs wrote: > Ahh right. I have just understood which part of the output I needed to > look at. However, for the ROI GLM there are only 1-2 regions that were > significantly different between groups, while the SPSS ANCOVA showed > significant group differences for the majority of parcellated regions. > I have confirmed that I am using the exact same model for each, so it > is only the analysis method that differs. Do you know why these two > methods would produce such disparate results? > > > Kind regards, > > Bronwyn Overs > Research Assistant > > Neuroscience Research Australia > > Neuroscience Research Australia > Margarete Ainsworth Building > Barker Street Randwick Sydney NSW 2031 Australia > *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 > > neura.edu.au <http://neura.edu.au> > > Follow @neuraustralia on twitter > <https://twitter.com/neuraustralia>Follow NeuRA on facebook > <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to > the NeuRA Magazine <http://www.neura.edu.au/help-research/subscribe> > > On 5/02/2015 3:16 am, Douglas N Greve wrote: >> I'm not sure that I understand what I'm looking at. If it is an ROI >> analysis, then there is no surface, it should be about 40 numbers, one >> for each ROI. >> >> On 02/03/2015 06:26 PM, Bronwyn Overs wrote: >>> Hi Doug, >>> >>> Thanks for your correction. >>> >>> I have now completed the FDR for my case-control comparisons, and it >>> appears that none of the regions survived. This is again quite >>> confusing given the large number of parcellated regions that survived >>> FDR in the SPSS ANCOVA. Can you confirm that this screenshot of the >>> sig.mgh file from ROI analysis looks as you would expect (it looks >>> very strange to me): >>> >>> >>> >>> Kind regards, >>> >>> Bronwyn Overs >>> Research Assistant >>> >>> Neuroscience Research Australia >>> >>> Neuroscience Research Australia >>> Margarete Ainsworth Building >>> Barker Street Randwick Sydney NSW 2031 Australia >>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>> >>> neura.edu.au<http://neura.edu.au> >>> >>> Follow @neuraustralia on twitter >>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to >>> the NeuRA Magazine<http://www.neura.edu.au/help-research/subscribe> >>> >>> On 4/02/2015 9:35 am, Douglas Greve wrote: >>>> Yes, it should be .^ >>>> >>>> On 2/3/15 5:33 PM, Bronwyn Overs wrote: >>>>> Hi Doug, >>>>> >>>>> I am having a problem with the line in Matlab 2014b: >>>>> p = 10^-abs(sigmat); >>>>> I keep getting the following error: >>>>> Error using ^ >>>>> Inputs must be a scalar and a square matrix. >>>>> To compute elementwise POWER, use POWER (.^) >>>>> instead. >>>>> >>>>> Do you know why this would be? >>>>> >>>>> Kind regards, >>>>> >>>>> Bronwyn Overs >>>>> Research Assistant >>>>> >>>>> Neuroscience Research Australia >>>>> >>>>> Neuroscience Research Australia >>>>> Margarete Ainsworth Building >>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>> >>>>> neura.edu.au<http://neura.edu.au> >>>>> >>>>> Follow @neuraustralia on twitter >>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to >>>>> the NeuRA Magazine<http://www.neura.edu.au/help-research/subscribe> >>>>> >>>>> On 4/02/2015 2:22 am, Douglas Greve wrote: >>>>>> There is not a way to do it from the command line. You can do it in >>>>>> matlab, something like >>>>>> >>>>>> sig = MRIread('sig.mgh'); >>>>>> sigmat = fast_vol2mat(sig); >>>>>> p = 10^-abs(sigmat); >>>>>> fdr = .05; >>>>>> pthresh = fast_fdrthresh(p,fdr); >>>>>> ind = find(p < pthresh); % This will be a list of ROI indices that >>>>>> survive FDR >>>>>> >>>>>> doug >>>>>> >>>>>> On 2/2/15 10:26 PM, Bronwyn Overs wrote: >>>>>>> Hi Doug, >>>>>>> >>>>>>> That makes perfect sense. Just one more thing then, how do you >>>>>>> conduct an FDR via the command line for an ROI mri_glmfit analysis? >>>>>>> >>>>>>> Kind regards, >>>>>>> >>>>>>> Bronwyn Overs >>>>>>> Research Assistant >>>>>>> >>>>>>> Neuroscience Research Australia >>>>>>> >>>>>>> Neuroscience Research Australia >>>>>>> Margarete Ainsworth Building >>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>> >>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>> >>>>>>> Follow @neuraustralia on twitter >>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe >>>>>>> to the NeuRA Magazine >>>>>>> <http://www.neura.edu.au/help-research/subscribe> >>>>>>> >>>>>>> On 3/02/2015 2:00 pm, Douglas Greve wrote: >>>>>>>> This is not something you would run the MC sim on because there >>>>>>>> is no clustering, it is just a list of ROIs with their p-values. >>>>>>>> The p-values are uncorrected. You can do bonferoni correction >>>>>>>> across all the ROIs (or just the ones you are interested in). You >>>>>>>> could do FDR too. >>>>>>>> >>>>>>>> doug >>>>>>>> >>>>>>>> >>>>>>>> On 2/2/15 9:39 PM, Bronwyn Overs wrote: >>>>>>>>> Thanks Doug, that worked well. >>>>>>>>> >>>>>>>>> However, is it possible to run a monte-carlo simulation with >>>>>>>>> this GLM ROI analysis? I attempted to run it using the following >>>>>>>>> command... >>>>>>>>> mri_glmfit-sim --glmdir >>>>>>>>> DesikanROIAnal_case-control.thick.lh.glmdir --cache 1.3 abs >>>>>>>>> --cwpvalthresh 0.05 --2spaces >>>>>>>>> and received the following error: >>>>>>>>> ERROR: could not determine file for >>>>>>>>> DesikanROIAnal_case-control.thick.lh.glmdir/mask >>>>>>>>> >>>>>>>>> Kind regards, >>>>>>>>> >>>>>>>>> Bronwyn Overs >>>>>>>>> Research Assistant >>>>>>>>> >>>>>>>>> Neuroscience Research Australia >>>>>>>>> >>>>>>>>> Neuroscience Research Australia >>>>>>>>> Margarete Ainsworth Building >>>>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>>>> >>>>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>>>> >>>>>>>>> Follow @neuraustralia on twitter >>>>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe to >>>>>>>>> the NeuRA Magazine >>>>>>>>> <http://www.neura.edu.au/help-research/subscribe> >>>>>>>>> >>>>>>>>> On 3/02/2015 11:03 am, Douglas Greve wrote: >>>>>>>>>> Even easier. Run aparcstats2table, then run mri_glmfit passing >>>>>>>>>> the output of aparcstats2table with --table (instead of --y). >>>>>>>>>> There's something on the wiki about it, also look for the ROI >>>>>>>>>> tutorial. >>>>>>>>>> doug >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> On 2/2/15 6:20 PM, Bronwyn Overs wrote: >>>>>>>>>>> Hi Doug, >>>>>>>>>>> >>>>>>>>>>> I am not sure how to run an ROI analysis using mri_glmfit. Is >>>>>>>>>>> there a wiki page detailing this method (I was unable to find >>>>>>>>>>> one)? Is the first step to map lh.aparc.label and >>>>>>>>>>> rh.aparc.label from fsaverage to each of my individual >>>>>>>>>>> subjects using mri_label2label? When I do so and then view the >>>>>>>>>>> mapped label for an individual subject in freeview, it appears >>>>>>>>>>> to be a continuous label for all of the parcellated regions >>>>>>>>>>> combined. Is this correct? >>>>>>>>>>> >>>>>>>>>>> Kind regards, >>>>>>>>>>> >>>>>>>>>>> Bronwyn Overs >>>>>>>>>>> Research Assistant >>>>>>>>>>> >>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>> >>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>> Margarete Ainsworth Building >>>>>>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>>>>>> >>>>>>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>>>>>> >>>>>>>>>>> Follow @neuraustralia on twitter >>>>>>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe >>>>>>>>>>> to the NeuRA Magazine >>>>>>>>>>> <http://www.neura.edu.au/help-research/subscribe> >>>>>>>>>>> >>>>>>>>>>> On 3/02/2015 3:31 am, Douglas Greve wrote: >>>>>>>>>>>> First, I would run the ROI analysis in mri_glmfit to see if >>>>>>>>>>>> you get the same results as in SPSS. In the handfull of these >>>>>>>>>>>> cases, no one has been able to correctly replicate the FS >>>>>>>>>>>> design matrix in SPSS, so I suspect that is part of the >>>>>>>>>>>> discrepancy. The other thing is that ROI and vertex-wise >>>>>>>>>>>> analyses are simply different. As an extreme example, if some >>>>>>>>>>>> of the vertices are pos and some are neg then they would >>>>>>>>>>>> cancel out when you average them in an ROI but individually >>>>>>>>>>>> could be significant at the vertex level. If you analyze the >>>>>>>>>>>> average over the cluster then that should come out as >>>>>>>>>>>> significant. >>>>>>>>>>>> >>>>>>>>>>>> doug >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On 2/1/15 11:36 PM, Bronwyn Overs wrote: >>>>>>>>>>>>> Dear FreeSurfer Mailing List, >>>>>>>>>>>>> >>>>>>>>>>>>> I have a sample of schizophrenia and control subjects for >>>>>>>>>>>>> whom I have run a case-control analysis of cortical >>>>>>>>>>>>> thickness using two separate methods (GLM vertex-wise >>>>>>>>>>>>> analysis in freesurfer, repeated measures ANCOVA analysis of >>>>>>>>>>>>> parcellated data in SPSS). However, for each methods of >>>>>>>>>>>>> analysis I am getting extremely different results. For the >>>>>>>>>>>>> GLM in Freesurfer I have only 1 small cluster in the frontal >>>>>>>>>>>>> lobe that differs between cases and controls (controlling >>>>>>>>>>>>> for all other IVs, FWMH = 10mm, cluster-forming threshold= >>>>>>>>>>>>> .05, cluster-wise pval=.05), while for the ANCOVA method all >>>>>>>>>>>>> but 8 of the parcellated regions differ significantly >>>>>>>>>>>>> between groups (p<.05). For both methods I have used the >>>>>>>>>>>>> same model of predictors (independent variables = gender, >>>>>>>>>>>>> group, scanning site; covariate = age) and exactly the same >>>>>>>>>>>>> sample of participants. I have also replicated the GLM >>>>>>>>>>>>> analysis using the QDEC GUI to ensure that I had no made any >>>>>>>>>>>>> mistakes. >>>>>>>>>>>>> >>>>>>>>>>>>> Can you provide any insight into why I would be seeing such >>>>>>>>>>>>> different results for each method using the same data set? >>>>>>>>>>>>> My findings using the ANCOVA analysis make much more sense >>>>>>>>>>>>> to me, given previous findings of reduced cortical thickness >>>>>>>>>>>>> in schizophrenia subjects. I was surprised not to find the >>>>>>>>>>>>> same pattern of effects using the GLM analysis. >>>>>>>>>>>>> -- >>>>>>>>>>>>> >>>>>>>>>>>>> Kind regards, >>>>>>>>>>>>> >>>>>>>>>>>>> Bronwyn Overs >>>>>>>>>>>>> Research Assistant >>>>>>>>>>>>> >>>>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>>>> >>>>>>>>>>>>> Neuroscience Research Australia >>>>>>>>>>>>> Margarete Ainsworth Building >>>>>>>>>>>>> Barker Street Randwick Sydney NSW 2031 Australia >>>>>>>>>>>>> *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265 >>>>>>>>>>>>> >>>>>>>>>>>>> neura.edu.au<http://neura.edu.au> >>>>>>>>>>>>> >>>>>>>>>>>>> Follow @neuraustralia on twitter >>>>>>>>>>>>> <https://twitter.com/neuraustralia>Follow NeuRA on facebook >>>>>>>>>>>>> <https://www.facebook.com/NeuroscienceResearchAustralia>Subscribe >>>>>>>>>>>>> to the NeuRA Magazine >>>>>>>>>>>>> <http://www.neura.edu.au/help-research/subscribe> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>> Freesurfer mailing list >>>>>>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>> Freesurfer mailing list >>>>>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> The information in this e-mail is intended only for the person to >>>>>>>>>>>> whom it is >>>>>>>>>>>> addressed. If you believe this e-mail was sent to you in error and >>>>>>>>>>>> the e-mail >>>>>>>>>>>> contains patient information, please contact the Partners >>>>>>>>>>>> Compliance HelpLine at >>>>>>>>>>>> http://www.partners.org/complianceline . If the e-mail was sent >>>>>>>>>>>> to you in error >>>>>>>>>>>> but does not contain patient information, please contact the >>>>>>>>>>>> sender and properly >>>>>>>>>>>> dispose of the e-mail. >>>>>>>>>>> _______________________________________________ >>>>>>>>>>> Freesurfer mailing list >>>>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>>>>>> _______________________________________________ >>>>>>>>>> Freesurfer mailing list >>>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> The information in this e-mail is intended only for the person to >>>>>>>>>> whom it is >>>>>>>>>> addressed. If you believe this e-mail was sent to you in error and >>>>>>>>>> the e-mail >>>>>>>>>> contains patient information, please contact the Partners Compliance >>>>>>>>>> HelpLine at >>>>>>>>>> http://www.partners.org/complianceline . If the e-mail was sent to >>>>>>>>>> you in error >>>>>>>>>> but does not contain patient information, please contact the sender >>>>>>>>>> and properly >>>>>>>>>> dispose of the e-mail. >>>>>>>>> _______________________________________________ >>>>>>>>> Freesurfer mailing list >>>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>>>> _______________________________________________ >>>>>>>> Freesurfer mailing list >>>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>>>> >>>>>>>> >>>>>>>> The information in this e-mail is intended only for the person to whom >>>>>>>> it is >>>>>>>> addressed. If you believe this e-mail was sent to you in error and the >>>>>>>> e-mail >>>>>>>> contains patient information, please contact the Partners Compliance >>>>>>>> HelpLine at >>>>>>>> http://www.partners.org/complianceline . If the e-mail was sent to >>>>>>>> you in error >>>>>>>> but does not contain patient information, please contact the sender >>>>>>>> and properly >>>>>>>> dispose of the e-mail. >>>>>>> _______________________________________________ >>>>>>> Freesurfer mailing list >>>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>> _______________________________________________ >>>>>> Freesurfer mailing list >>>>>> Freesurfer@nmr.mgh.harvard.edu >>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>> >>>>>> >>>>>> The information in this e-mail is intended only for the person to whom >>>>>> it is >>>>>> addressed. If you believe this e-mail was sent to you in error and the >>>>>> e-mail >>>>>> contains patient information, please contact the Partners Compliance >>>>>> HelpLine at >>>>>> http://www.partners.org/complianceline . If the e-mail was sent to you >>>>>> in error >>>>>> but does not contain patient information, please contact the sender and >>>>>> properly >>>>>> dispose of the e-mail. >>>>> _______________________________________________ >>>>> Freesurfer mailing list >>>>> Freesurfer@nmr.mgh.harvard.edu >>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>> _______________________________________________ >>>> Freesurfer mailing list >>>> Freesurfer@nmr.mgh.harvard.edu >>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>> >>>> >>>> The information in this e-mail is intended only for the person to whom it >>>> is >>>> addressed. If you believe this e-mail was sent to you in error and the >>>> e-mail >>>> contains patient information, please contact the Partners Compliance >>>> HelpLine at >>>> http://www.partners.org/complianceline . If the e-mail was sent to you >>>> in error >>>> but does not contain patient information, please contact the sender and >>>> properly >>>> dispose of the e-mail. >>> _______________________________________________ >>> Freesurfer mailing list >>> Freesurfer@nmr.mgh.harvard.edu >>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer -- Douglas N. 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