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Combined permutation test and mixed-effect model for group average analysis in fMRI.

Abstract : In group average analyses, we generalize the classical one-sample t test to account for heterogeneous within-subject uncertainties associated with the estimated effects. Our test statistic is defined as the maximum likelihood ratio corresponding to a Gaussian mixed-effect model. The test's significance level is calibrated using the same sign permutation framework as in Holmes et al., allowing for exact specificity control under a mild symmetry assumption about the subjects' distribution. Because our likelihood ratio test does not rely on homoscedasticity, it is potentially more sensitive than both the standard t test and its permutation-based version. We present results from the Functional Imaging Analysis Contest 2005 dataset to support this claim.
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https://hal-cea.archives-ouvertes.fr/cea-00333698
Contributor : Alexis Roche <>
Submitted on : Thursday, October 23, 2008 - 5:54:31 PM
Last modification on : Wednesday, September 16, 2020 - 4:53:34 PM

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Sébastien Mériaux, Alexis Roche, Ghislaine Dehaene-Lambertz, Bertrand Thirion, Jean-Baptiste Poline. Combined permutation test and mixed-effect model for group average analysis in fMRI.. Human Brain Mapping, Wiley, 2006, 27 (5), pp.402-10. ⟨10.1002/hbm.20251⟩. ⟨cea-00333698⟩

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