Designing observational studies for credible causal inference in addiction research-Directed acyclic graphs, modified disjunctive cause criterion and target trial emulation
- PMID: 38343103
- DOI: 10.1111/add.16442
Designing observational studies for credible causal inference in addiction research-Directed acyclic graphs, modified disjunctive cause criterion and target trial emulation
Abstract
Randomized controlled trials (RCTs) are considered the gold standard for causal inference. With a sufficient sample size, randomization removes confounding up to the time of randomization and allows the treatment effect to be isolated. However, RCTs may have limited generalizability and transportability and are often not feasible in addiction research due to ethical or logistical constraints. The importance of observational studies from real-world settings has been increasingly recognized in research on health. This paper provides an overview of modern approaches to designing observational studies that enable causal inference. It illustrates three key techniques, Directed Acyclic Graphs (DAGs), modified Disjunctive Cause Criterion and Target Trial Emulation, and discusses the strengths and limitations of their applications.
Keywords: DAGs; casuality; causal inference; directed acyclic graphs; modified disjunctive cause criterion; target trial emulation.
© 2024 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.
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