Meaningful Associations Redux: Quantifying and interpreting effect size in the context of the Adolescent Brain and Cognitive Development study
Anthony Steven Dick, Jonathan S. Comer, Mohammadreza Bayat, Marilyn Curtis, Timothy Hayes, Shannon M. Pruden, Samuel W. Hawes, Raul Gonzalez, Angela R. Laird, Paulo A. Graziano

TL;DR
This paper discusses how to interpret effect sizes in large-scale studies like the ABCD Study to improve scientific rigor and reproducibility.
Contribution
The paper introduces a four-part framework for evaluating effect sizes to enhance interpretation and communication in large-scale developmental research.
Findings
Large datasets like ABCD can produce statistically significant but trivial effects.
A framework is proposed to define meaningful effect sizes and improve scientific practices.
Visualizing results enhances interpretation and communication in developmental research.
Abstract
The Adolescent Brain Cognitive Development (ABCD) Study represents a pioneering initiative that aims to unravel the complexities of behavioral and neural development in youth. In this paper, we address the challenges inherent in extracting meaningful insights from the extensive data compiled by the ABCD initiative. Our focus is on advocating for best practices in reproducible research, interpretation of effect size, and reporting of principled results. Central to this discourse is a detailed examination of effect sizes within the expansive ABCD dataset, and how they can be meaningfully interpreted in the context of large-scale research. We describe the hurdles associated with transitioning from conventional small-sample studies to the opportunities and challenges of large samples, including the phenomenon of statistically significant but practically trivial effects. To promote…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCognitive Abilities and Testing · Psychometric Methodologies and Testing · Meta-analysis and systematic reviews
