A blueprint for synthetic control methodology: a causal inference tool for evaluating natural experiments in population health

Barr, Ben ORCID: 0000-0002-4208-9475, Zhang, Xingna ORCID: 0000-0002-8849-2112, Green, Mark ORCID: 0000-0002-0942-6628 and Buchan, Iain ORCID: 0000-0003-3392-1650 (2022) A blueprint for synthetic control methodology: a causal inference tool for evaluating natural experiments in population health BMJ-BRITISH MEDICAL JOURNAL, 379. o2712-. ISSN 0959-535X, 1756-1833

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Abstract

Interventions in emergencies such as the covid-19 pandemic may need rapid supporting evidence. Randomised trials in these situations are often impractical to design or deliver. One technique for estimating the causal effect of an intervention using observational data is the synthetic control method. This article outlines the method and its assumptions, best practice interpretation, and application.

Item Type:	Article
Uncontrolled Keywords:	Humans, Causality, Population Health
Divisions:	Faculty of Health & Life Sciences Faculty of Health & Life Sciences > Inst. Population Health
Depositing User:	Symplectic Admin
Date Deposited:	28 Nov 2022 09:59
Last Modified:	16 Jun 2026 05:50
DOI:	10.1136/bmj.o2712
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3166404
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