Comparing Propensity Score Methods Versus Traditional Regression Analysis for the Evaluation of Observational Data: A Case Study Evaluating the Treatment of Gram-Negative Bloodstream Infections | Zendy

Joe Amoah | Zendy; Elizabeth A. Stuart | Zendy; Sara E. Cosgrove | Zendy; Anthony Harris | Zendy; Jennifer Han | Zendy; Ebbing Lautenbach | Zendy; Pranita D. Tamma | Zendy

Open Access

Comparing Propensity Score Methods Versus Traditional Regression Analysis for the Evaluation of Observational Data: A Case Study Evaluating the Treatment of Gram-Negative Bloodstream Infections

Author(s) -

Joe Amoah,

Elizabeth A. Stuart,

Sara E. Cosgrove,

Anthony Harris,

Jennifer Han,

Ebbing Lautenbach,

Pranita D. Tamma

Publication year - 2020

Publication title -

clinical infectious diseases

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.44

H-Index - 336

eISSN - 1537-6591

pISSN - 1058-4838

DOI - 10.1093/cid/ciaa169

Subject(s) - medicine , propensity score matching , observational study , gram , regression analysis , bloodstream infection , intensive care medicine , statistics , mathematics , genetics , bacteria , biology

Propensity score methods are increasingly being used in the infectious diseases literature to estimate causal effects from observational data. However, there remains a general gap in understanding among clinicians on how to critically review observational studies that have incorporated these analytic techniques.

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