Frontiers in NeuroinformaticsBioinformaticsPeer-reviewed journal article
ABCDscores: An R package for computing summary scores in the ABCD Study(R)
Le ZhangiD, Olivier Celhay, Biplabendu DasiD, Samantha BermaniD, Laura R. ZiemeriD, Calen J. Smith, Shermaine AbadiD, Anders Martin DaleiD, Janosch LinkersdörferiD
Abstract
The ABCD Study(R) is the largest longitudinal research study of brain development and child health across the United States. The study generates a rich multimodal dataset, including file-based raw and derivative data and a curated tabulated dataset comprising data from a broad spectrum of research domains. Historically, summary scores in the tabulated dataset were computed using the electronic data capture system REDCap or external scripting solutions. However, this approach was rigid, unreliable, and lacked transparency around how scores were computed. Here, we introduce ABCDscores, an R software package that is used by the study to compute most non-proprietary summary scores included in the tabulated ABCD data resource and allows for customization to meet specific research needs. ABCDscores provides a flexible, open-source solution that uses R for transparent and reproducible scoring. The package is built to apply standard scoring methods across different types of assessments, ensuring consistent and accurate results even with large datasets. By simplifying complex scoring procedures into a user-friendly process, ABCDscores streamlines research workflows, reduces errors, and saves researchers valuable time. The package aims to improve analyses of data from the ABCD Study(R) and can serve as a model for the development of similar tools and a standardized framework for other research studies, fostering new discoveries and innovation in the field.
- assay: electronic health records
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
- Citations
- 2
- FWCI
- 8.38
- Field percentile
- top 6%
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