Our analyses reveal that optimizing study design is pivotal for increasing standardized effect sizes and replicability in Brain-wide association studies, where sample size and design significantly influence outcomes.
Modifying study design through effective sampling schemes can enhance standardized effect sizes across various brain measures, ultimately allowing for better understanding of brain-behaviour relationships.
We found that common longitudinal models may inadvertently reduce replicability by conflating between-subject and within-subject changes; instead, explicit modeling of these effects is crucial for accurate analyses.
The large sample sizes and diverse datasets evaluated in our study provide strong evidence for the necessity of well-designed BWAS, contributing significantly to the robustness of findings in neuroscience.
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