Missing data approaches for longitudinal neuroimaging research: Examples from the Adolescent Brain and Cognitive Development (ABCD) Study®.

ABSTRACT: This paper addresses the challenges of managing missing values within expansive longitudinal neuroimaging datasets, using the specific example of data derived from the Adolescent Brain and Cognitive Development (ABCD) Study^®. The conventional listwise deletion method, while widely used, is not recommended due to the risk that substantial bias can potentially be introduced with this method. Unfortunately, recommended alternative practices can be challenging to implement with large datasets. In this paper, we advocate for the adoption of more sophisticated statistical methodologies, including multiple imputation, propensity score weighting, and full information maximum likelihood (FIML). Through practical examples and code using ABCD Study^® data, we illustrate some of t

SUBMITTER: Li L 

PROVIDER: S-EPMC12688060 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature