Confidence Sets for Cohen’s d effect size images

Abstract

Highlights Confidence Sets (CSs) extend the idea of confidence intervals to fMRI maps. For a Cohen’s threshold upper CS asserts where lower CS where . We demonstrate the CSs method on HCP subject-level Cohen’s d data. We compare the CSs with results from standard statistical voxelwise inference. Unlike traditional cluster tests, CSs precisely quantify spatial uncertainty.

Improving the replicability of neuroimaging findings by thresholding effect sizes instead of p‐values

“…Our proposed methods still rely on hypothesis testing using SEI so are not completely free of the limitations of PVT. For imaging, modern approaches that construct confidence sets using effect size thresholding approaches or Bayesian inference procedures hold promise as true alternatives to PVT-based inference for neuroimaging (Bowring et al, 2019(Bowring et al, , 2021Chen et al, 2019;Sommerfeld, Sain, & Schwartzman, 2018). Our suggestions here of EST demonstrates the advantage of considering alternatives to classical PVT.…”

“…In this article, we argue for using an effect size-based CFT, instead of a threshold based on a p-value. Our suggestion is motivated by increasing criticism of PVT in the context of hypothesis testing and an increased interest in potential alternatives (Bowring et al, 2019;Bowring, Telschow, Schwartzman, & Nichols, 2021;Chen et al, 2019;Chen, Taylor, & Cox, 2017;Wasserstein & Lazar, 2016;Wasserstein, Schirm, & Lazar, 2019). This approach resolves the limitations of PVT stated above: (a) Using effect size thresholding (EST), the set of voxels that are identified as activated in an analysis does not depend on the sample size, so it improves the consistency of the target regions of activation across studies.…”

Brain-Wide Inferiority and Equivalence Tests in fMRI Group Analyses: Selected Applications

“…See also Bowring et al (2021). Please note that for conventional one-sample t-tests √ ′( ′ ) − = √ 1 and DoF=n-1, and for conventional two-sample t-tests √ ′( ′…”

“…In contrast, with a very high number of participants an analysis will in most cases deliver a large number of significant voxels. In most cases it is also conceptually more interesting to know whether the activation of a brain region is more or less strongly associated with a specific behavior or intervention (see for example Bowring et al, 2019;Bowring et al, 2021).…”

“…Such approaches have so far rarely been applied to MRI data (see Bowring et al, 2021;Pardoe et al, 2016;Reggev et al, 2020 for examples). With this paper we want to contribute to the use of this important statistical method in fMRI research.…”