Dear Stef,
You could use ImCalc to compute linear combinations of your
within-subjects images. Otherwise, as you mention, you could obtain the
same images from a GLM, even if inefficiently: enter all of your images
in a GLM where the design matrix is the identity matrix (e.g. a one-way
ANOVA with one image per cell, assuming sphericity) and use contrasts to
create the images of interest.
Best regards,
Guillaume.
On 04/01/2019 09:50, Stef Meliss wrote:
> Dear Guillaume,
>
>
>
> I have a (very basic) follow up question.
>
>
>
> I would like to perform VBM analysis in a 2(Group: Experimental vs
> Control) x 2 (Time point: pre vs post) mixed design. How do I specify
> the first level in the context of VBM? Would I simply set up a t-test
> containing the images for each time point separately for each subject
> and then specify the contrasts as described? Or should I use the fMRI
> First Level specification to do that?
>
>
>
> Many thanks in advance,
>
> Stef
>
>
>
> *From: *"SPM (Statistical Parametric Mapping)" <[log in to unmask]> on
> behalf of "Flandin, Guillaume" <[log in to unmask]>
> *Reply-To: *"Flandin, Guillaume" <[log in to unmask]>
> *Date: *Tuesday, 4 December 2018 at 17:51
> *To: *"[log in to unmask]" <[log in to unmask]>
> *Subject: *Re: [SPM] Flexible factorial design
>
>
>
> Dear Geneviève,
>
>
>
> The document mentioned by the reviewer is actually published as a
>
> chapter of the SPM book. I also list further references that you might
>
> find useful.
>
>
>
> Penny, W. & Henson, R.N. (2006). Analysis of Variance. In K. Friston, J.
>
> Ashburner, S. Kiebel, T. Nichols, and W. Penny (Eds), Statistical
>
> Parametric Mapping: The analysis of functional brain images. Elsevier,
>
> London, 2006.pp. 166-177.
>
> http://www.mrc-cbu.cam.ac.uk//personal/rik.henson/personal/PennyHenson_SPM_06b.pdf
> <http://www.mrc-cbu.cam.ac.uk/personal/rik.henson/personal/PennyHenson_SPM_06b.pdf>
>
>
>
> Henson, R.N (2015) Analysis of Variance (ANOVA). In: Arthur W. Toga,
>
> editor. Brain Mapping: An Encyclopedic Reference, vol. 1, pp. 477-481.
>
> Academic Press: Elsevier.
>
> http://www.mrc-cbu.cam.ac.uk/wp-content/uploads/2015/03/Henson_EN_15_ANOVA.pdf
>
>
>
> Friston, K.J. et al (2002) Classical and Bayesian Inference in
>
> Neuroimaging: Applications. NeuroImage. 16:484-512.
>
> https://doi.org/10.1006/nimg.2002.1091
>
>
>
> McFarquhar, M. (2018, April 10). Modelling group-level repeated measures
>
> of neuroimaging data using the univariate general linear model.
>
> https://doi.org/10.31234/osf.io/a5469
>
>
>
> Flexible factorial design is indeed SPM terminology and refers to an
>
> option in the interface to specify the design matrix (and non-sphericity
>
> assumptions) of a GLM.
>
> Instructions for a 2x2 mixed ANOVA are given here:
>
> https://en.wikibooks.org/wiki/SPM/Group_Analysis
>
>
>
> Best wishes,
>
> Guillaume.
>
>
>
> On 22/11/2018 11:49, Genevieve Allaire-Duquette wrote:
>
> Hi,
>
> I recently submitted a manuscript where I used a "random effects
> flexible-factorial design" with one within-subject and one
> between-subject factor (2X2) in SPM8.
>
> One reviewer criticized the approach (see below) and I'd like to
> know if there is some relevant literature I could use to explain the
> model better.
>
> Many thanks,
>
> Geneviève Allaire-D.
>
> *
>
> The use of "random effects flexible-factorial" is not given a
> published citation so one looks for supporting literature. The SPM8
> manual only describes this modeling nonstatistically, in section
> 10.2.8. Henson and Penny's Technical Report (2003? 2005?)
> (https://www.fil.ion.ucl.ac.uk/~wpenny/publications/rik_anova.pdf)
> does not make any note of the flexible-factorial concept, and where
> it is available on the web it seems not to be elucidated in detail.
>
> No other software product appears to use the phrase, and it is not
> in common parlance. Thus, it will have to be explained to the
> readership in much finer detail to be interpretable here.
>
> Moreover, a recent critique by Chen et al (Neuroimage
> 2014, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4121851/) shows
> that SPM is hindered by serious limitations and can readily
> overestimate significance.
>
>
>
> --
>
> Guillaume Flandin, PhD
>
> Wellcome Centre for Human Neuroimaging
>
> UCL Queen Square Institute of Neurology
>
> London WC1N 3BG
>
>
>
--
Guillaume Flandin, PhD
Wellcome Centre for Human Neuroimaging
UCL Queen Square Institute of Neurology
London WC1N 3BG
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