Hi,
I think you want the marsbar mailing list for this one rather than the SPM list.
On Wed, Oct 9, 2013 at 12:07 PM, Hu, Sien <[log in to unmask]> wrote:
> Dear MarsBaR members,
>
> I have a question on the MarsBaR analysis. I got the barch script from the MarsBaR FAQ under 'How do I run a MarsBaR analysis in batch mode?'. The structure marsS from 'compute_contrasts' stores many things including con, stat, and p, and etc. If I want to use a value to represent subject's performance on a specific ROI, should I use the 'con' value or the 'stat' value?
It depends what you are interested in. Remember the t statistic is
the con value divided by the variability of the con value estimate.
It's not normally distributed except for high degrees of freedom. It
reflects something like the signal divided by the noise. You might
prefer the con value if you want an estimate of the signal regardless
of the noise. It should be normally distributed if the errors are
normally distributed and the null hypothesis is true. The F statistic
is always positive so it is not normally distributed; likewise the F
statistic con value is always positive - so these can be hard to use
for further testing.
> Another related question is that, when I use the function 'getdata' on a contrast image of interest, the mean of Y is very similar to what is returned by marsS.con(contrast_number), but not completely identical. I thought that the rationale is the same for the way to get marsS from 'compute_contrasts' and the Y from 'getdata' so ideally marsS.con(contrast_number) should be identical to Y. Is this correct? Or I'm understanding it in a wrong way?
>
You mean you have done an SPM analysis of contrast N and have a con
image, and you've done a marsbar analysis of the same contrast?
They won't always be the same because marsbar will usually reestimate
the autocorrelation estimates for the time series in this ROI, whereas
SPM uses autocorrelation estimates from all the 'activated' brain
voxels at the same time. See:
http://marsbar.sourceforge.net/faq.html#how-do-i-do-a-random-effect-analysis-in-marsbar
Cheers,
Matthew
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