Hi there -
I'm not sure what this is ( or how to compute it ).
If you can give us the equations describing this, we should be able to
tell you how to compute it with the Feat output.
What is it that you would like to describe with "Standardized Beta
weights", that you can't describe with the original Betas and the t-stats?
Sorry I'm no use
T
On Tue, 12 Aug 2003, Edward Vessel wrote:
> No, I am referring not to a t or z score, but to a regression weight.
> A standardized Beta weight is never greater than one. It is a 'factor
> loading' so to speak.
>
> Ed
>
> On Tuesday 12 August 2003 01:16 am, Tim Behrens wrote:
> > Hi there - by standardised beta weight, do you mean the t-statistic?
> >
> > You can get these post-hoc using Feat, by just running the
> > contrast-manager (by selecting Post-Stats from the top right menu,
> > clicking on the Post-Stats tab, and selecting "Edit Contrasts").
> >
> > If you want to get them by hand, you were nearly right, you have to
> > divide the copes by the square root of the varcopes (i.e. the standard
> > error on the copes).
> >
> > If you want them to be truly sandardised (i.e. z-scores), you have to
> > account for the degrees of freedom, you can do this with ttoz
> >
> > ttoz -zout zoutput varcope cope dof
> >
> >
> >
> > Hope this answers your question
> >
> > cheers
> >
> > Tim
> >
> > On Mon, 11 Aug 2003, Edward Vessel wrote:
> > > Hi folks -
> > >
> > > How would one go about computing a standardized beta weight (in the
> > > regression sense) from a cope or pe?
> > >
> > > If I am correct, the pe's are (unstandardized) regression weights (b's).
> > > Therefore, I'd need to multiply by the standard deviation of the
> > > predictor and divide by the standard deviation of the data. But I am
> > > unsure which files would correspond to this.
> > >
> > > The varcope seems to be not just be the deviation of the predictor, as
> > > that should be the same for all voxels. It also isn't the standard
> > > deviation of the data, as this would be the same for all predictors. Is
> > > it a ratio of the two?
> > >
> > > If that is the case, then do I just divide the cope by the varcope to get
> > > a standardized weight?
> > >
> > > I'm not interested in getting percent signal change in this case ... it
> > > is a continuously varying parameter (from 0 to 1), so I'd like to get a
> > > beta weight (or even part correlation).
> > >
> > > Ed
> > >
> > > --
> > > Ed Vessel
> > > U. of Southern California [log in to unmask]
> > > Dept. of Neuroscience
> > > HNB, 3641 Watt Way http://geon.usc.edu/~vessel
> > > Los Angeles, CA 90089-2520
> > > (213) 740-6102
>
>
--
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Tim Behrens
Centre for Functional MRI of the Brain
The John Radcliffe Hospital
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Oxford University
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