Propensity score methods in observational research: brief review and guide for authors

Causal inference in observational research requires a careful approach to adjustment for confounding. One such approach is the use of propensity score analyses. In this editorial, we focus on the role of propensity score-based methods in estimating causal effects from non-randomised observational da...

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Bibliographic Details
Published inBritish journal of anaesthesia : BJA Vol. 131; no. 5; pp. 805 - 809
Main Authors Andrew, Benjamin Y., Alan Brookhart, M., Pearse, Rupert, Raghunathan, Karthik, Krishnamoorthy, Vijay
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 01.11.2023
Subjects
causal inference
Causality
confounding
Data Interpretation, Statistical
Humans
observational research
Observational Studies as Topic
Propensity Score
propensity score methods
statistics
observational research
confounding
causal inference
propensity score methods
statistics
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Summary:Causal inference in observational research requires a careful approach to adjustment for confounding. One such approach is the use of propensity score analyses. In this editorial, we focus on the role of propensity score-based methods in estimating causal effects from non-randomised observational data. We highlight the details, assumptions, and limitations of these methods and provide authors with guidelines for the conduct and reporting of propensity score analyses.
Bibliography:SourceType-Other Sources-1
content type line 63
ObjectType-Editorial-2
ObjectType-Commentary-1
ISSN:0007-0912
1471-6771
DOI:10.1016/j.bja.2023.06.054