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Cited by 69

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

A systematic review of propensity score methods in the acute care surgery literature: avoiding the pitfalls and proposing a set of reporting guidelines

Zakrison, T. L., Austin, P. C., McCredie, V. A.·2018·European Journal of Trauma and Emergency Surgery
DOI 10.1007/s00068-017-0786-6
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Show all 5 references

Research works printed but not linked: 19

  1. McMurry TL, Hu Y, Blackstone EH, Kozower BD. Propensity scores: methods, considerations, and applications in the. Journal of Thoracic Cardiovascular Surgery. J Thorac Cardiovasc Surg. 2015;150(1):14–9. · DOI
  2. Luo Z, Gardiner JC, Bradley CJ. Applying propensity score methods in medical research: pitfalls and prospects. Med Care Res Rev. 2010;67(5):528–54. · DOI
  3. Austin PC. The relative ability of different propensity score methods to balance measured covariates between treated and untreated subjects in observational studies. Med Decis Mak. 2009;29(6):661–77. · DOI
  4. Austin PC. A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003. Stat Med. 2008;27(12):2037–49. · DOI · Paper page
  5. Austin PC. Primer on statistical interpretation or methods report card on propensity-score matching in the cardiology literature from 2004 to 2006: a systematic review. Circ Cardiovasc Qual Outcomes. 2008;1(1):62–7. · DOI
  6. Austin PC. Propensity-score matching in the cardiovascular surgery literature from 2004 to 2006: a systematic review and suggestions for improvement. J Thorac Cardiovasc Surg. 2007;134(5):1128–35. · DOI
  7. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535. · DOI · Paper page
  8. Gayat E, Pirracchio R, Resche-Rigon M, Mebazaa A, Mary JY, Porcher R. Propensity scores in intensive care and anaesthesiology literature: a systematic review. Intensive Care Med. 2010;36(12):1993–2003. · DOI
  9. Inoue J, Shiraishi A, Yoshiyuki A, Haruta K, Matsui H, Otomo Y. Resuscitative endovascular balloon occlusion of the aorta might be dangerous in patients with severe torso trauma: a propensity score analysis. J Trauma Acute Care Surg. 2016;80(4):559–67. · DOI
  10. Austin PC, Grootendorst P, Anderson GM. A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study. Stat Med. 2007;26(4):734–53. · DOI
  11. Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm Stat. 2011;10(2):150–61. · DOI · Paper page
  12. Austin PC. Some methods of propensity-score matching had superior performance to others: results of an empirical investigation and Monte Carlo simulations. Biom J. 2009;51(1):171–84. · DOI · Paper page
  13. Austin PC. The performance of different propensity score methods for estimating marginal odds ratios. Stat Med. 2007;26(16):3078–94. · DOI
  14. Austin PC. The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments. Stat Med. 2014;33(7):1242–58. · DOI
  15. Morgan SL, Todd JL. A diagnostic routine for the detection of consequential heterogeneity of causal effects. Sociol Methodol. 2008;38:231–81. · DOI
  16. Mitra R, Reiter JP. A comparison of two methods of estimating propensity scores after multiple imputation. Stat Methods Med Res. 2016;25(1):188–204. · DOI
  17. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70(1):41–55. · DOI · Paper page
  18. Rassen JA, Shelat AA, Myers J, Glynn RJ, Rothman KJ, Schneeweiss S. One-to-many propensity score matching in cohort studies. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 2):69–80. · DOI
  19. Austin PC, Mamdani MM, Stukel TA, Anderson GM, Tu JV. The use of the propensity score for estimating treatment effects: administrative versus clinical data. Stat Med. 2005;24(10):1563–78. · DOI

Cited by

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Metadata

Authors
Zakrison, T. L., Austin, P. C., & McCredie, V. A.
Venue
European Journal of Trauma and Emergency Surgery
Publisher
Springer Science and Business Media LLC
Published
2017-03-24
Volume
44
Issue
3
Pages
385-395
ISSN
  • 1863-9933
  • 1863-9941
DOI
10.1007/s00068-017-0786-6
Cited by
69
References
5
Language
en
Licence
www.springer.com/tdm (unspecified)

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CoChat. (2026). Citation check: A systematic review of propensity score methods in the acute care surgery literature: avoiding the pitfalls and proposing a set of reporting guidelines. https://app.cochat.ai/papers/10.1007/s00068-017-0786-6
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Zakrison, T. L., Austin, P. C., & McCredie, V. A. (2018). A systematic review of propensity score methods in the acute care surgery literature: avoiding the pitfalls and proposing a set of reporting guidelines. European Journal of Trauma and Emergency Surgery. https://doi.org/10.1007/s00068-017-0786-6

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.