Mixed-effect statistics for group analysis in fMRI: a nonparametric maximum likelihood approach. - Archive ouverte HAL Access content directly
Journal Articles NeuroImage Year : 2007

Mixed-effect statistics for group analysis in fMRI: a nonparametric maximum likelihood approach.

(1) , , ,
1
Alexis Roche
  • Function : Author
  • PersonId : 854989
Sébastien Mériaux
  • Function : Author
Merlin Keller
  • Function : Author
Bertrand Thirion

Abstract

This technical note describes a collection of test statistics accounting for estimation uncertainties at the within-subject level, that can be used as alternatives to the standard t statistic in one-sample random-effect analyses, i.e. when testing the mean effect of a population. We build such test statistics by estimating the across-subject distribution of the effects using maximum likelihood under a nonparametric mixed-effect model. For inference purposes, the statistics are calibrated using permutation tests to achieve exact false positive control under a symmetry assumption regarding the across-subject distribution. The new tests are implemented in a freely available toolbox for SPM called Distance.

Dates and versions

cea-00333625 , version 1 (23-10-2008)

Identifiers

Cite

Alexis Roche, Sébastien Mériaux, Merlin Keller, Bertrand Thirion. Mixed-effect statistics for group analysis in fMRI: a nonparametric maximum likelihood approach.. NeuroImage, 2007, 38 (3), pp.501-10. ⟨10.1016/j.neuroimage.2007.06.043⟩. ⟨cea-00333625⟩
89 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More