Enhancing causal inference in population-based neuroimaging data in children and adolescents.

ABSTRACT: Recent years have seen the increasing availability of large, population-based, longitudinal neuroimaging datasets, providing unprecedented capacity to examine brain-behavior relationships in the neurodevelopmental context. However, the ability of these datasets to deliver causal insights into brain-behavior relationships relies on the application of purpose-built analysis methods to counter the biases that otherwise preclude causal inference from observational data. Here we introduce these approaches (i.e., propensity score-based methods, the 'G-methods', targeted maximum likelihood estimation, and causal mediation analysis) and conduct a review to determine the extent to which they have been applied thus far in the field of developmental cognitive neuroscience. We identify just eight rele

SUBMITTER: Visontay R 

PROVIDER: S-EPMC11541429 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature