Dear FSL group,
We are planning to perform a seed-based RSFC analysis consisting of 4 ACC seeds, in which all the seeds would be included in one model. However, given that the GLM will be used for statistical inferences, we are wondering whether multicollinearity may occur, as the seeds (our regressors) are correlated? If so, what would be the best strategy to deal with this issue:
1. Perform separate analysis for each seed instead of putting them all in the same model/analysis.
2. Put all the seeds in one model and orthogonalize their time series with respect to each other, and with respect to the nuisance covariates, to ensure that the time series for each seed reflected its unique variance.
Any assistance would be greatly appreciated.
Regards,
Mark
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