Applying Propensity Score Methods in Clinical Research in Neurology

doi:10.1212/WNL.0000000000012777

. 2021 Nov 2;97(18):856-863.

doi: 10.1212/WNL.0000000000012777. Epub 2021 Sep 9.

Applying Propensity Score Methods in Clinical Research in Neurology

Peter C Austin¹, Amy Ying Xin Yu², Manav V Vyas², Moira K Kapral²

Affiliations

¹ From ICES (P.C.A., A.Y.X.Y., M.V.V., M.K.K.), Toronto; Institute of Health Management, Policy and Evaluation (P.C.A., M.K.K.) and Divisions of Neurology (A.Y.X.Y., M.V.V.) and General Internal Medicine (M.K.K.), Department of Medicine, University of Toronto; and Sunnybrook Research Institute (P.C.A.), Toronto, Canada. peter.austin@ices.on.ca.
² From ICES (P.C.A., A.Y.X.Y., M.V.V., M.K.K.), Toronto; Institute of Health Management, Policy and Evaluation (P.C.A., M.K.K.) and Divisions of Neurology (A.Y.X.Y., M.V.V.) and General Internal Medicine (M.K.K.), Department of Medicine, University of Toronto; and Sunnybrook Research Institute (P.C.A.), Toronto, Canada.

PMID: 34504033
PMCID: PMC8610625
DOI: 10.1212/WNL.0000000000012777

Applying Propensity Score Methods in Clinical Research in Neurology

Peter C Austin et al. Neurology. 2021.

. 2021 Nov 2;97(18):856-863.

doi: 10.1212/WNL.0000000000012777. Epub 2021 Sep 9.

Authors

Peter C Austin¹, Amy Ying Xin Yu², Manav V Vyas², Moira K Kapral²

Affiliations

¹ From ICES (P.C.A., A.Y.X.Y., M.V.V., M.K.K.), Toronto; Institute of Health Management, Policy and Evaluation (P.C.A., M.K.K.) and Divisions of Neurology (A.Y.X.Y., M.V.V.) and General Internal Medicine (M.K.K.), Department of Medicine, University of Toronto; and Sunnybrook Research Institute (P.C.A.), Toronto, Canada. peter.austin@ices.on.ca.
² From ICES (P.C.A., A.Y.X.Y., M.V.V., M.K.K.), Toronto; Institute of Health Management, Policy and Evaluation (P.C.A., M.K.K.) and Divisions of Neurology (A.Y.X.Y., M.V.V.) and General Internal Medicine (M.K.K.), Department of Medicine, University of Toronto; and Sunnybrook Research Institute (P.C.A.), Toronto, Canada.

PMID: 34504033
PMCID: PMC8610625
DOI: 10.1212/WNL.0000000000012777

Abstract

Propensity score-based analysis is increasingly being used in observational studies to estimate the effects of treatments, interventions, and exposures. We introduce the concept of the propensity score and how it can be used in observational research. We describe 4 different ways of using the propensity score: matching on the propensity score, inverse probability of treatment weighting using the propensity score, stratification on the propensity score, and covariate adjustment on the propensity score (with a focus on the first 2). We provide recommendations for the use and reporting of propensity score methods for the conduct of observational studies in neurologic research.

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Figures

**Figure 1. Author Checklist for the Design and Analysis of Studies Using Propensity Score Methods**

**Figure 2. Author Checklist for the Reporting of Studies Using Propensity Score Methods**

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References

1. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41-55.
1. Austin PC. An introduction to propensity-score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399-424. - PMC - PubMed
1. Westreich D, Cole SR. Invited commentary: positivity in practice. Am J Epidemiol. 2010;171(6):674-677; discussion 678-681. - PMC - PubMed
1. Vyas MV, Austin PC, Fang J, Laupacis A, Silver FL, Kapral MK. Immigration status, ethnicity, and long-term outcomes following ischemic stroke. Neurology. 2021;96(8):e1145-e1155. - PubMed
1. Austin PC, Grootendorst P, Anderson GM. A comparison of the ability of different propensity score models to balance measured variables between treated and untreated participants: a Monte Carlo study. Stat Med. 2007;26(4):734-753. - PubMed

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[1] Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41-55.

[2] Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41-55.

[3] Austin PC. An introduction to propensity-score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399-424. - PMC - PubMed

[4] Austin PC. An introduction to propensity-score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399-424. - PMC - PubMed

[5] Westreich D, Cole SR. Invited commentary: positivity in practice. Am J Epidemiol. 2010;171(6):674-677; discussion 678-681. - PMC - PubMed

[6] Westreich D, Cole SR. Invited commentary: positivity in practice. Am J Epidemiol. 2010;171(6):674-677; discussion 678-681. - PMC - PubMed

[7] Vyas MV, Austin PC, Fang J, Laupacis A, Silver FL, Kapral MK. Immigration status, ethnicity, and long-term outcomes following ischemic stroke. Neurology. 2021;96(8):e1145-e1155. - PubMed

[8] Vyas MV, Austin PC, Fang J, Laupacis A, Silver FL, Kapral MK. Immigration status, ethnicity, and long-term outcomes following ischemic stroke. Neurology. 2021;96(8):e1145-e1155. - PubMed

[9] Austin PC, Grootendorst P, Anderson GM. A comparison of the ability of different propensity score models to balance measured variables between treated and untreated participants: a Monte Carlo study. Stat Med. 2007;26(4):734-753. - PubMed

[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 participants: a Monte Carlo study. Stat Med. 2007;26(4):734-753. - PubMed

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Applying Propensity Score Methods in Clinical Research in Neurology

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Applying Propensity Score Methods in Clinical Research in Neurology

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