Abstract
We propose a method for the statistical analysis of fMRI data that seeks a compromise between efficiency, generality, validity, simplicity and execution speed. The main differences between this analysis and previous ones are: a simple bias reduction and regularization for voxel-wise autoregressive model parameters; the combination of effects and their estimated standard deviations across different scans/sessions/subjects via a hierarchical random effects analysis using the EM algorithm; overcoming the problem of a small number of scans/session/subjects using a regularized variance ratio to increase the degrees of freedom.