Hi all -
I'm running parallel analyses on a two-modality experiment (fMRI, fNIRS) that consists of two sessions. For the fMRI analysis, I'm combining the two sessions in FSL with a fixed effects model as described here:
https://fsl.fmrib.ox.ac.uk/fslcourse/lectures/practicals/feat2/index.html#multisession
I'd like to combine the two fNIRS session in a statistically identical way. For a given NIRS channel, I have a beta estimate for each run (and the variance for that estimate). I'd like to put those two estimates and their variances into the analogous fixed effects model to what I'm doing in FSL and get back a combined beta estimate and its variance/error. The FSL help offers this:
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The FE option implements a standard weighted fixed effects model. No random effects variances are modelled or estimated. The FE error variances are the variances (varcopes) from the previous level. Weighting is introduced by allowing these variances to be unequal (heteroscedastic). Degrees-of-freedom are calculated by summing the effective degrees-of-freedom for each input from the previous level and subtracting the number of higher-level regressors.
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Does anyone know where I might find some more details on that implementation so that I might recreate it by hand?
Thanks very much for any help!
Aaron
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