Study design features that improve effect sizes in cross-sectional and longitudinal brain-wide association studies.

Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behavior associations. Several recent studies showed that thousands of study participants are required to improve the replicability of BWAS because actual effect sizes are much smaller than those reported in smaller studies. Here, we perform a meta-analysis of a robust effect size index (RESI) using 63 longitudinal and cross-sectional magnetic resonance imaging studies (75,255 total scans) to demonstrate that optimizing study design is an important way to improve standardized effect sizes in BWAS. Our results of brain volume associations with demographic and cognitive variables indicate that BWAS with larger standard deviation of the independent variable have larger effect size estimates and that longitudinal studies have systematically larger standardized effect sizes than cross-sectional studies by 290%. We propose a crosssectional RESI to adjust for the systematic difference in effect sizes between cross-sectional and longitudinal studies that allows investigators to quantify the benefit of conducting their study longitudinally. Using bootstrapping in the Lifespan Brain Chart Consortium we show that modifying study design to increase between-subject standard deviation by 45% increases standardized effect sizes by 42% and adding a second measurement per subject can increase effect sizes by 35%. These findings underscore the importance of considering design features in BWAS and emphasize that increasing sample size is not the only approach to improve the replicability of BWAS.