Brain-wide inferiority and equivalence tests in fMRI group analyses: Selected applications.

ABSTRACT: Null hypothesis significance testing is the major statistical procedure in fMRI, but provides only a rather limited picture of the effects in a data set. When sample size and power is low relying only on strict significance testing may lead to a host of false negative findings. In contrast, with very large data sets virtually every voxel might become significant. It is thus desirable to complement significance testing with procedures like inferiority and equivalence tests that allow to formally compare effect sizes within and between data sets and offer novel approaches to obtain insight into fMRI data. The major component of these tests are estimates of standardized effect sizes and their confidence intervals. Here, we show how Hedges' g, the bias corrected version of Cohen's d, and its c

SUBMITTER: Gerchen MF 

PROVIDER: S-EPMC8596945 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature