A review of the use of propensity score diagnostics in papers published in high-ranking medical journals
Abstract 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...
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doaj-356c94e7ec7241b39a6e376b1ba1cbdf2020-11-25T02:15:38ZengBMCBMC Medical Research Methodology1471-22882020-05-012011910.1186/s12874-020-00994-0A review of the use of propensity score diagnostics in papers published in high-ranking medical journalsEmily Granger0Tim Watkins1Jamie C. Sergeant2Mark Lunt3Centre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of ManchesterDepartment of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South WalesCentre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of ManchesterCentre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of ManchesterAbstract 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.http://link.springer.com/article/10.1186/s12874-020-00994-0Covariate balanceConfoundingPropensity scoresDiagnosticsEpidemiology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Emily Granger Tim Watkins Jamie C. Sergeant Mark Lunt |
spellingShingle |
Emily Granger Tim Watkins Jamie C. Sergeant Mark Lunt A review of the use of propensity score diagnostics in papers published in high-ranking medical journals BMC Medical Research Methodology Covariate balance Confounding Propensity scores Diagnostics Epidemiology |
author_facet |
Emily Granger Tim Watkins Jamie C. Sergeant Mark Lunt |
author_sort |
Emily Granger |
title |
A review of the use of propensity score diagnostics in papers published in high-ranking medical journals |
title_short |
A review of the use of propensity score diagnostics in papers published in high-ranking medical journals |
title_full |
A review of the use of propensity score diagnostics in papers published in high-ranking medical journals |
title_fullStr |
A review of the use of propensity score diagnostics in papers published in high-ranking medical journals |
title_full_unstemmed |
A review of the use of propensity score diagnostics in papers published in high-ranking medical journals |
title_sort |
review of the use of propensity score diagnostics in papers published in high-ranking medical journals |
publisher |
BMC |
series |
BMC Medical Research Methodology |
issn |
1471-2288 |
publishDate |
2020-05-01 |
description |
Abstract 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. |
topic |
Covariate balance Confounding Propensity scores Diagnostics Epidemiology |
url |
http://link.springer.com/article/10.1186/s12874-020-00994-0 |
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