Cited by 657Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyMeta-analysis and systematic reviews

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Alternative approaches for confounding adjustment in observational studies using weighting based on the propensity score: a primer for practitioners

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Desai, Rishi J, Franklin, Jessica M·2019·BMJ

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Abstract

This report aims to provide methodological guidance to help practitioners select the most appropriate weighting method based on propensity scores for their analysis out of many available options (eg, inverse probability treatment weights, standardised mortality ratio weights, fine stratification weights, overlap weights, and matching weights), and outlines recommendations for transparent reporting of studies using weighting based on the propensity scores.

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Desai, 2019, An empirical evaluation of a propensity score stratification based weighting approach in settings of more than two treatment groups, Pharmacoepidemiol Drug Saf, 28, 19

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Authors: Desai, R. J., & Franklin, J. M.
Affiliations: Brigham and Women's Hospital (US)
Corresponding author: Desai, Rishi J
ORCID: Desai, Rishi J
Franklin, Jessica M
Venue: BMJ
Publisher: BMJ
Published: 2019-10-23
Volume: 367
Pages: l5657
ISSN: 1756-1833 (ISSN-L)
0959-8138
DOI: 10.1136/bmj.l5657
OpenAlex: W2982188023
Cited by: 657
References: 31
Citations by year: 2026: 76 · 2025: 142 · 2024: 117 · 2023: 108 · 2022: 108 · 2021: 78 · 2020: 26
FWCI: 41.26
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.bmj.com/company/legal-information/terms-conditions/legal-information/tdm-licencepolicy (tdm)
Locations: BMJ (publishedVersion)
PubMed (publishedVersion)
HighWire Press Open Archive (submittedVersion)
Funders: Brigham and Women's Hospital
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords: propensity score weighting, confounding adjustment, observational studies, reporting transparency, causal inference
MeSH terms: Data Interpretation, Statistical, Humans, Research Design, Confounding Factors, Epidemiologic, Survival Rate, Logistic Models, Treatment Outcome, Practice Guidelines as Topic, Propensity Score, Observational Studies as Topic

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Alternative approaches for confounding adjustment in observational studies using weighting based on the propensity score: a primer for practitioners

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