Group Analysis with Both Individual Effect and Within- Subject Variability
نویسندگان
چکیده
Data analysis in FMRI could be performed in one grand multilevel model that incorporates both withinand cross-subjects variabilities. However, it is due to the presence of both variance components that such a nonlinear model makes computation currently impractical, forcing analysts to adopt a two-stage approach: individual analysis with a time series regression model that explores activations in individual brains, and group analysis that integrates the results from all subjects.
منابع مشابه
FMRI group analysis combining effect estimates and their variances
Conventional functional magnetic resonance imaging (FMRI) group analysis makes two key assumptions that are not always justified. First, the data from each subject is condensed into a single number per voxel, under the assumption that within-subject variance for the effect of interest is the same across all subjects or is negligible relative to the cross-subject variance. Second, it is assumed ...
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