Using Directed Acyclic Graphs in Observational Research: A Practical Guide for Paediatric Researchers Publisher Pubmed

Summary: Can diagrams improve causal research in children? A guide says causal diagrams can expose assumptions and prevent faulty adjustments. #CausalInference #Pediatrics

Smith M J ; Mansournia M A
Source: Archives of Disease in Childhood Published:2026

Abstract

Directed acyclic graphs (DAGs) are increasingly recommended or required by journals for observational studies making causal claims yet few paediatric observational studies present DAGs to support their analytical approach. This practical guide addresses the implementation gap between methodological guidance and research practice by clarifying when DAGs are needed (causal questions only, not descriptive or predictive research), demonstrating how to construct them for paediatric studies, and explaining how to use them to identify appropriate statistical adjustment strategies. We illustrate common pitfalls, including adjusting for colliders and mediators, address practical challenges such as temporal ordering ambiguity, and provide a worked example from recent paediatric literature. Proper use of DAGs makes causal assumptions explicit, prevents common analytical errors and strengthens causal inference in observational paediatric research. © Author(s) (or their employer(s)) 2026. No commercial re-use. See rights and permissions. Published by BMJ Group.