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Hi Manfred and Guillaume, Regarding number of factors I was referring to the full factorial. It only allows us to have three factors in it. Is that correct? K On Mon, May 14, 2018 at 10:34 AM, Manfred Klöbl < [log in to unmask]> wrote: > Dear Karina, > > I'm not aware of a limitation in factor numbers in SPM. At least in SPM12 > I can create an arbitrary number of factors by simply adding them under > "Factors" in flexible factorial model setup. Regarding the dependency > settings, I misunderstood your study design. You are right, "Face" and > "Emotion" are of course dependent variables as they represent data from the > same subject. > > Best, > Manfred > > Am 07.05.2018 um 18:40 schrieb Karina Quevedo: > > Dear Manfred, > Ok, let me rephrase: > Use flexible factorial keep in mind however that we have 3 factors > already: Time (Pre Post), Emotion (Happy, Neutral Sad) Face (Self and > Other), how do we add the 4th factor of subjects when SPM12 only allows us > to model 3 factors? > If we model Emotion and Face and independent is a bit of a > miss-representation because is the same task before and after something, > but even if we do that we can't model 4 factors. > Though perhaps I am missing something in your text that allows for > modeling all 4? > Warmly, > K > > On Mon, May 7, 2018 at 11:33 AM, Manfred Klöbl < > [log in to unmask]> wrote: > >> Dear Karina, >> >> since this is a repeated-measures design, you need to include subject >> factors to adjust for the dependencies and get the degrees of freedom >> right. I would hence suggest to use the flexible factorial setup. Time, >> self / other and the emotions can be represented as factors there. "Time" >> would be a dependent factor, the others are independent. You can also make >> setting up the model easier for you by using the "subject" and "repl" >> keywords in SPM. For the variance settings, inter-group factors are often >> assumed to have unequal and intra-group factors equal variance. However, >> this is just a rule of thumb. >> >> Best, >> Manfred >> >> Am 07.05.2018 um 18:14 schrieb Karina Quevedo: >> >> Dear SPM brethren, >> Ok we figured out what the difference was between them. Indeed the first >> level analysis images were different! - due to an error in the batch script >> automatic processing. >> Now that this has been solved we would be very grateful for your advice >> regarding how not to loose any level of our design: >> Time, Self and Emotion, >> Warmly, >> Karina >> >> On Mon, May 7, 2018 at 10:24 AM, Karina Quevedo <[log in to unmask]> wrote: >> >>> Dear Toben, Manfred, and Guillaume >>> >>> I have attached the job file for both batches with this email. >>> Please notice that the variance and covariance matrix are not the same. >>> Batch 1 seems to have more collinearity compared to batch 2 between the >>> columns. That is what we got when we explore the covariance structure. >>> >>> Warmly, >>> Karina >>> >>> On Mon, May 7, 2018 at 10:10 AM, Karina Quevedo <[log in to unmask]> >>> wrote: >>> >>>> Dear Guillaume, >>>> We will do the detective work today and tomorrow. In the mean time how >>>> would you recommend analyzing the data? >>>> *We do not want to loose any of the conditions (time, self, or >>>> emotion). And we want to have them all in the same model.* >>>> Warmly and more soon on those first level images, >>>> Karina >>>> >>>> On Mon, May 7, 2018 at 9:56 AM, Guillaume Flandin <[log in to unmask]> >>>> wrote: >>>> >>>>> Dear Karina, >>>>> >>>>> From what I can see in your two second-level SPM.mat files, the GLMs >>>>> seem to be the same (same design matrix and same variance components) >>>>> so, as Volkmar and Torben pointed out, the difference must be in your >>>>> input images. Are you really sure that they are identical? For example, >>>>> are these two images from the first level identical: >>>>> RT-FMRI/3007_RT1/1stLevel/ESOM_PRE/con_0013.nii >>>>> RT-FMRI/SmO/3007/1stLevel/ESOM_PRE_SmO_Rest/con_0044.nii >>>>> >>>>> I would still probably recommend to analyse the data differently at the >>>>> second level but that's something we can discuss once the detective >>>>> work >>>>> is over. >>>>> >>>>> Best regards, >>>>> Guillaume. >>>>> >>>>> >>>>> On 07/05/18 10:51, Torben Lund wrote: >>>>> > Dear Karina >>>>> > >>>>> > In the batch manager hit the save icon, and save each of the batch >>>>> jobs >>>>> > if you have not already done so, with those files we can se what you >>>>> > actually specified. >>>>> > >>>>> > Best >>>>> > Torben >>>>> > >>>>> > >>>>> >> Den 6. maj 2018 kl. 19.56 skrev Karina Quevedo <[log in to unmask] >>>>> >> <mailto:[log in to unmask]>>: >>>>> >> >>>>> >> Dear Torben, Volkmar and Manfred, >>>>> >> Please see attached in a zip drive the screen shot of the matrix and >>>>> >> covariance structure and the design matrix information. SPM12 is >>>>> >> taking different decisions for the covariance structure for two sets >>>>> >> of images that we are fairly certain that we calculated in the same >>>>> >> way in parallel to check our process. >>>>> >> We are going to run the 1st level images a third time. >>>>> >> >>>>> >> Torben we know that the second level job batches have not been >>>>> >> specified in the same way already but happy to shared them with you. >>>>> >> >>>>> >> Essentially we ran the same batch (Batch 1) but uploaded a second >>>>> >> different set of 1st level contrast images for QA (which we derived >>>>> >> with the same fmri structure to begin with) and SPM took different >>>>> >> decisions automatically regarding the var-covar structure. >>>>> >> >>>>> >> If we did something wrong we just want to know what it is and why >>>>> the >>>>> >> difference? >>>>> >> Warmly? >>>>> >> Karina >>>>> >> >>>>> >> On Sun, May 6, 2018 at 5:29 AM, Torben Lund <[log in to unmask] >>>>> >> <mailto:[log in to unmask]>> wrote: >>>>> >> >>>>> >> Dear Karina >>>>> >> >>>>> >> if you could share the two batch jobs then we could confirm, >>>>> that >>>>> >> they have been indeed been specified the same way. If they have >>>>> >> been specified the same way I think there is a problem with SPM, >>>>> >> but I don’t really think this is the case. >>>>> >> >>>>> >> >>>>> >> Best >>>>> >> Torben >>>>> >> >>>>> >> >>>>> >> >>>>> >>> Den 5. maj 2018 kl. 21.41 skrev Karina Quevedo < >>>>> [log in to unmask] >>>>> >>> <mailto:[log in to unmask]>>: >>>>> >>> >>>>> >>> Dear Volkmar, Torben and Manfred, >>>>> >>> We specify the same settings for variance in both models but we >>>>> >>> did used different images for estimating the two different >>>>> >>> models. However see the details before about how we estimated >>>>> the >>>>> >>> two sets of images. (GRACIAS!) >>>>> >>> >>>>> >>> We are analyzing a complex set of data that has the following >>>>> >>> design structure, >>>>> >>> >>>>> >>> *_Pre_*: Participants see their own face and a stranger's face >>>>> >>> across 3 emotions (happy, neutral and sad) >>>>> >>> *_ >>>>> >>> _* >>>>> >>> *_Intervention_*: Participants attempt to change their >>>>> Bilateral >>>>> >>> Amygdala and Hippocampus (ROI) activity via a neurofeedback >>>>> >>> procedure: >>>>> >>> >>>>> >>> Condition 1: See the Self face and increase ROI. >>>>> >>> Condition 2: See the Other face and count backwards. >>>>> >>> *_ >>>>> >>> _* >>>>> >>> *_Post_*: Participants see their own face and a stranger's face >>>>> >>> across 3 emotions (happy, neutral and sad). >>>>> >>> >>>>> >>> We are interested in analyzing the data *Pre versus Post*, and >>>>> we >>>>> >>> used a *F**ull Factorial Design with 3 factors: Time, Face and >>>>> >>> Emotion.* >>>>> >>> >>>>> >>> The columns in the attached matrixes are as follows 1 Face a= >>>>> >>> self, b= other, 2 Emotion a=happy, b=neutral, c=sad. >>>>> >>> Column 1: Pre, 1a, 2a >>>>> >>> Column 2: Pre, 1a, 2b >>>>> >>> Column 3: Pre, 1a, 2c >>>>> >>> Column 4: Pre. 1b, 2a >>>>> >>> Column 5: Pre, 1b, 2b >>>>> >>> Column 6: Pre, 1b, 2c >>>>> >>> Column 7: Post, 1a, 2a >>>>> >>> Column 8: Post, 1a, 2b >>>>> >>> Column 9: Post, 1a, 2c >>>>> >>> Column 10: Post. 1b, 2a >>>>> >>> Column 11: Post, 1b, 2b >>>>> >>> Column 12: Post, 1b, 2c >>>>> >>> >>>>> >>> The first level analysis contrasts that we used to create these >>>>> >>> second level full factorial batches are coming from the same >>>>> >>> source in terms of pre-processing files. >>>>> >>> >>>>> >>> The only difference is that we calculated the first level >>>>> >>> contrast twice (using the same pre-processing data and initial >>>>> >>> fmri factorial specification ) and for one of the sets of first >>>>> >>> level analysis batches (_*after using the same initial fmri >>>>> >>> factorial design specification*_) we calculated more follow up >>>>> t >>>>> >>> contrasts. That was all. >>>>> >>> >>>>> >>> However when we run two parallel second level analysis with >>>>> those >>>>> >>> two sets of first level contrasts we are getting very different >>>>> >>> results because SPM 12 seems to be choosing to model the data >>>>> >>> differently in terms of covariance structure: >>>>> >>> >>>>> >>> *Batch 1 *in the figure we attach is the batch using images >>>>> >>> derived from 1st level batches where we calculated less t >>>>> >>> contrasts. SPM created a covariance matrix that assumes >>>>> >>> higher collinearity between column 1 an column 7 (i.e. Pre >>>>> >>> Happy Self Face, and Post Happy Self Face). It gives a >>>>> value >>>>> >>> of *cosine = -0.75*. >>>>> >>> >>>>> >>> *Batch 2* in the figure we attach is the batch using images >>>>> >>> derived from 1st level batches where we calculated more t >>>>> >>> contrasts. Using the same initial Batch 1 but loading the >>>>> >>> different images, it seems that SPM 12 created a different >>>>> >>> covariance structure. *Cosine = -0.08* (more orthogonal >>>>> >>> compared to Batch 1) >>>>> >>> >>>>> >>> >>>>> >>> In addition to that, we had also looked into the SPM.mat file >>>>> for >>>>> >>> both of the second level batches. We took a screenshot of the >>>>> >>> SPM.xX.W values for both batches. If you would like, we could >>>>> >>> send you the SPM.mat batches for you to look at. >>>>> >>> >>>>> >>> Our questions are: >>>>> >>> 1. Why is SPM 12 making such different decisions with regards >>>>> to >>>>> >>> covariance structures? >>>>> >>> >>>>> >>> 2. Given our design which model is more appropriate Batch 1 or >>>>> >>> Batch 2? >>>>> >>> >>>>> >>> 3. We cannot run a flexible factorial design without loosing >>>>> one >>>>> >>> of our conditions (in order to model participants). Is that >>>>> still >>>>> >>> ok? >>>>> >>> >>>>> >>> One of our colleges is adamant about running a flexible >>>>> factorial >>>>> >>> but that means that we will lose either emotion or self in the >>>>> >>> design, We think that the best model is *Batch 1* because it >>>>> >>> assumes _*more *_collinearity between the*Pre and the Post >>>>> >>> conditions*, what is your opinion? >>>>> >>> >>>>> >>> Warmly yours, >>>>> >>> Karina >>>>> >>> <design matrix information SPM_xX_W.jpg> >>>>> >>> <matrix and covariate structures.jpg> >>>>> >>> >>>>> >>> >>>>> >>> On Wed, May 2, 2018 at 4:37 AM, Volkmar Glauche >>>>> >>> <[log in to unmask] >>>>> >>> <mailto:[log in to unmask]>> wrote: >>>>> >>> >>>>> >>> Dear Karina, >>>>> >>> >>>>> >>> as Torben said, something seems to be different. Did you >>>>> >>> really specify the same settings for variance ((un)equal) >>>>> >>> and independence (yes/no) in both models? Did you use the >>>>> >>> same factors when specifying the models? Are both models >>>>> >>> estimated on the same set of images? Since non-sphericity >>>>> >>> estimation depends on the data, different input data may >>>>> >>> yield different non-sphericity estimates. >>>>> >>> You may also want to use "Review Design" to look at the >>>>> >>> effects of model estimation. You will find a "Design" menu >>>>> in >>>>> >>> the interactive window, where you can explore the design >>>>> >>> matrix, files and factors and covariance structure. When >>>>> >>> looking at the covariance structure, a multi-page image >>>>> >>> matrix will be displayed. On the first page, you will find >>>>> >>> the estimated covariance and on the following pages the >>>>> >>> individual covariance components for which parameters have >>>>> >>> been estimated. >>>>> >>> >>>>> >>> Best, >>>>> >>> Volkmar >>>>> >>> >>>>> >>> >>>>> >>> >>>>> >>> >>>>> >>> -- >>>>> >>> Karina Quevedo, Ph.D., L.P. >>>>> >>> Assistant Professor. Division of Child and Adolescent >>>>> Psychiatry >>>>> >>> Room F260 >>>>> >>> University of Minnesota. Department of Psychiatry >>>>> >>> 2450 Riverside Avenue, Mpls, MN 55454 >>>>> >>> <https://maps.google.com/?q=2450+Riverside+Avenue,+Mpls,+MN >>>>> +55454&entry=gmail&source=g> >>>>> >>> 612 >>>>> <https://maps.google.com/?q=2+450%2BRiverside%2BAvenue,%2BMpls,%2BMN+%2B55454&entry=gmail&source=g> >>>>> -2 >>>>> <https://maps.google.com/?q=2+450%2BRiverside%2BAvenue,%2BMpls,%2BMN+%2B55454&entry=gmail&source=g>73-9761 >>>>> Fax: 612-273-9779 >>>>> >>> [log in to unmask] <mailto:[log in to unmask]> >>>>> >>> >>>>> >> >>>>> >> >>>>> >> >>>>> >> >>>>> >> -- >>>>> >> Karina Quevedo, Ph.D., L.P. >>>>> >> Assistant Professor. Division of Child and Adolescent Psychiatry >>>>> >> Room F260 >>>>> >> University of Minnesota. Department of Psychiatry >>>>> >> 2450 Riverside Avenue, Mpls, MN 55454 >>>>> >> 612-273-9761 Fax: 612-273-9779 >>>>> >> [log in to unmask] <mailto:[log in to unmask]> >>>>> >> >>>>> >> <matrix and covariate structures.zip> >>>>> > >>>>> >>>>> -- >>>>> Guillaume Flandin, PhD >>>>> Wellcome Centre for Human Neuroimaging >>>>> University College London >>>>> 12 Queen Square >>>>> <https://maps.google.com/?q=12+Queen+Square+%0D%0A++++++++++++++++++++++++++++++++++++London+WC1N+3BG&entry=gmail&source=g> >>>>> London WC1N 3BG >>>>> >>>> >>>> >>>> >>>> -- >>>> Karina Quevedo, Ph.D., L.P. >>>> Assistant Professor. Division of Child and Adolescent Psychiatry >>>> Room F260 >>>> University of Minnesota. Department of Psychiatry >>>> 2450 Riverside Avenue, Mpls, MN 55454 >>>> 612-273-9761 Fax: 612-273-9779 >>>> [log in to unmask] >>>> >>>> >>> >>> >>> -- >>> Karina Quevedo, Ph.D., L.P. >>> Assistant Professor. Division of Child and Adolescent Psychiatry >>> Room F260 >>> University of Minnesota. Department of Psychiatry >>> 2450 Riverside Avenue, Mpls, MN 55454 >>> <https://maps.google.com/?q=2450+Riverside+Avenue,+Mpls,+MN+55454&entry=gmail&source=g> >>> 612-273-9761 Fax: 612-273-9779 >>> [log in to unmask] >>> >>> >> >> >> -- >> Karina Quevedo, Ph.D., L.P. >> Assistant Professor. Division of Child and Adolescent Psychiatry >> Room F260 >> University of Minnesota. Department of Psychiatry >> 2450 Riverside Avenue, Mpls, MN 55454 >> <https://maps.google.com/?q=2450+Riverside+Avenue,+Mpls,+MN+55454&entry=gmail&source=g> >> 612-273-9761 Fax: 612-273-9779 >> [log in to unmask] >> >> > > > -- > Karina Quevedo, Ph.D., L.P. > Assistant Professor. Division of Child and Adolescent Psychiatry > Room F260 > University of Minnesota. Department of Psychiatry > 2450 Riverside Avenue, Mpls, MN 55454 > <https://maps.google.com/?q=2450+Riverside+Avenue,+Mpls,+MN+55454&entry=gmail&source=g> > 612-273-9761 Fax: 612-273-9779 > [log in to unmask] > > -- Karina Quevedo, Ph.D., L.P. Assistant Professor. Division of Child and Adolescent Psychiatry Room F260 University of Minnesota. Department of Psychiatry 2450 Riverside Avenue, Mpls, MN 55454 612-273-9761 Fax: 612-273-9779 [log in to unmask] ######################################################################## To unsubscribe from the SPM list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=SPM&A=1