This is just straight-forward GLM, ie,
beta = inv(X'*X)*X'*y (y is the input time series after preproc)
yhat = X*beta
residual = y - yhat
residualstd = sum(residual.^2)/DOF (DOF = rows of X - cols of X)
t = C*beta/sqrt(C'*inv(X'*X)*C*residualstd)
where C is the contrast matrix

On 3/10/2023 4:50 PM, haoran.x@gmail.com wrote:

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Hi,

I have a naïve question. When I use GLM for a single subject timeseries data, how the variance is evaluated to get the t value? I know the beta values and contrast matrix make the numerator for the t value. How is the denominator made? Is it through the fitting residual ie std(residual), or is it from session by session or run by run variance? Can I find the formula somewhere? I was not able to find the answer in tutorial or the existing mailing list. Thanks a lot!

Best,

Haoran
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