Semiparametric confidence sets for cross-sectional and longitudinal neuroimaging.

ABSTRACT: The majority of neuroimaging inference focuses on hypothesis testing rather than effect estimation. With concerns about replicability, there is growing interest in reporting standardized effect sizes from neuroimaging group-level analyses. Confidence sets for effect sizes were recently developed for neuroimaging, but are restricted to simple univariate contrasts (e.g., one-sample or two-sample test Cohen's d) and cross-sectional data. Thus, existing methods exclude increasingly common longitudinal associations of biological brain measurements with, potentially nonlinear, inter- and intra-individual variations in diagnosis, development, or symptoms. We use modern methods for confidence sets combined with a recently proposed robust effect size index to provide a very general approach and sof

SUBMITTER: Zhang X 

PROVIDER: S-EPMC12580815 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature