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dc.contributor.authorGranger, Emily; orcid: 0000-0003-0134-1467; email: emily.granger-2@postgrad.manchester.ac.uk
dc.contributor.authorWatkins, Tim
dc.contributor.authorSergeant, Jamie C.
dc.contributor.authorLunt, Mark
dc.date.accessioned2021-05-27T15:32:05Z
dc.date.available2021-05-27T15:32:05Z
dc.date.issued2020-05-27
dc.date.submitted2019-07-10
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/624731/12874_2020_Article_994_nlm.xml?sequence=2
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/624731/additional-files.zip?sequence=3
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/624731/12874_2020_Article_994.pdf?sequence=4
dc.identifier.citationBMC Medical Research Methodology, volume 20, issue 1, page 132
dc.identifier.urihttp://hdl.handle.net/10034/624731
dc.descriptionFrom Springer Nature via Jisc Publications Router
dc.descriptionHistory: received 2019-07-10, accepted 2020-04-26, registration 2020-04-27, pub-electronic 2020-05-27, online 2020-05-27, collection 2020-12
dc.descriptionPublication status: Published
dc.descriptionFunder: Medical Research Council (UK); Grant(s): 1789957
dc.description.abstractAbstract: Background: Propensity scores are widely used to deal with confounding bias in medical research. An incorrectly specified propensity score model may lead to residual confounding bias; therefore it is essential to use diagnostics to assess propensity scores in a propensity score analysis. The current use of propensity score diagnostics in the medical literature is unknown. The objectives of this study are to (1) assess the use of propensity score diagnostics in medical studies published in high-ranking journals, and (2) assess whether the use of propensity score diagnostics differs between studies (a) in different research areas and (b) using different propensity score methods. Methods: A PubMed search identified studies published in high-impact journals between Jan 1st 2014 and Dec 31st 2016 using propensity scores to answer an applied medical question. From each study we extracted information regarding how propensity scores were assessed and which propensity score method was used. Research area was defined using the journal categories from the Journal Citations Report. Results: A total of 894 papers were included in the review. Of these, 187 (20.9%) failed to report whether the propensity score had been assessed. Commonly reported diagnostics were p-values from hypothesis tests (36.6%) and the standardised mean difference (34.6%). Statistical tests provided marginally stronger evidence for a difference in diagnostic use between studies in different research areas (p = 0.033) than studies using different propensity score methods (p = 0.061). Conclusions: The use of diagnostics in the propensity score medical literature is far from optimal, with different diagnostics preferred in different areas of medicine. The propensity score literature may improve with focused efforts to change practice in areas where suboptimal practice is most common.
dc.languageen
dc.publisherBioMed Central
dc.rightsLicence for this article: http://creativecommons.org/licenses/by/4.0/
dc.sourceeissn: 1471-2288
dc.subjectResearch Article
dc.subjectData collection, quality, and reporting
dc.subjectCovariate balance
dc.subjectConfounding
dc.subjectPropensity scores
dc.subjectDiagnostics
dc.subjectEpidemiology
dc.titleA review of the use of propensity score diagnostics in papers published in high-ranking medical journals
dc.typearticle
dc.date.updated2021-05-27T15:32:05Z
dc.date.accepted2020-04-26


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