Thank you for the clarification Mark. One last point: are multiple regression designs permissible (e.g., with a group variable as well as a couple covariates)?
cheers
roman
> Date: Mon, 2 May 2011 21:45:44 +0100
> From: [log in to unmask]
> Subject: Re: [FSL] FIRST shape analysis, correlation and statistical interpretation
> To: [log in to unmask]
>
> Dear Tugan and Roman,
>
> The output from a FIRST vertex analysis is always an F-statistic.
> It runs a multivariate GLM and this is the output of that MV-GLM
> procedure (using Pillai's Trace). I'm not sure where you found the
> sentence about "strength of correlation" but this was not meant to
> indicate that it was a correlation coefficient - it was meant in a
> non-technical sense, such that the F-statistic reflect the residual
> correlation of the variable of interest after factoring out any other
> confounding effects.
>
> The short answer is that you will be seeing F-statistics, and you
> can run FDR on this without problem.
>
> You might also find the newly published paper on FIRST helpful
> for clarifying how the multivariate GLM works. The paper details
> are:
>
> Patenaude, B., Smith, S.M., Kennedy, D., and Jenkinson M.
> A Bayesian Model of Shape and Appearance for Subcortical Brain
> NeuroImage, 56(3):907-922, 2011.
>
> http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WNP-527PRMC-2&_user=10&_coverDate=06%2F01%2F2011&_rdoc=8&_fmt=high&_orig=browse&_origin=browse&_zone=rslt_list_item&_srch=doc-info(%23toc%236968%232011%23999439996%233153734%23FLA%23display%23Volume)&_cdi=6968&_sort=d&_docanchor=&_ct=101&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=0880a49ea45171f2e3298d396fc83dc1&searchtype=a
>
> All the best,
> Mark
>
>
>
> On 2 May 2011, at 21:31, Roman M wrote:
>
> > re-post.
> >
> > Since I would like to hear the answer to that too..
> >
> > thank you
> >
> > Roman
> >
> > > Date: Wed, 20 Apr 2011 17:36:04 +0100
> > > From: [log in to unmask]
> > > Subject: [FSL] FIRST shape analysis, correlation and statistical interpretation
> > > To: [log in to unmask]
> > >
> > > Hi,
> > >
> > > I wanted to clarify if I am interpreting the output of shape analysis correctly when I used correlation and how I can derive meaningful statistics.
> > >
> > > I am studying age associated changes and I get great looking results. But when it came to interpretation, I went and read the FIRST manual, the thesis, the paper and numerous email discussions. What I understand is, the color bar represents F-stats only if I did an analysis looking at group differences. If I am exploring shape changes that are correlated with age, the colors "represent the strength of correlation". But it does not look like any correlation coefficient and I presume an F-statistic was not derived from the CC, either. Is there a way to derive a meaningful (publishable) statistics off of this? It seems that I cannot run FDR on it, either, since the outcome is not a statistic image.
> > >
> > > I will be grateful if someone can shed a light on this.
> > >
> > > best,
> > >
> > > Tugan
