Prognostic score–based balance measures can be a useful diagnostic for propensity score methods in comparative effectiveness research
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TLDR
Prognostic score-based balance measures should be considered for assessing the performance of propensity score methods for reducing bias in nonexperimental studies, and prognostic scores displayed the highest correlations with bias of all the balance measures considered.About:
This article is published in Journal of Clinical Epidemiology.The article was published on 2013-08-01 and is currently open access. It has received 385 citations till now. The article focuses on the topics: Propensity score matching & Matching (statistics).read more
Citations
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Journal ArticleDOI
Methods for constructing and assessing propensity scores.
Melissa M. Garrido,Melissa M. Garrido,M.S.H.S. Amy S. Kelley M.D.,M.S.H.S. Amy S. Kelley M.D.,B A Julia Paris,B A Katherine Roza,Diane E. Meier,R. Sean Morrison,R. Sean Morrison,Melissa D. Aldridge,Melissa D. Aldridge +10 more
TL;DR: Propensity scores are one useful tool for accounting for observed differences between treated and comparison groups and careful testing of propensity scores is required before using them to estimate treatment effects.
Journal ArticleDOI
Balance diagnostics after propensity score matching
TL;DR: The methods used for assessing balance in covariates after PSM are outlined, which include standardized mean difference (SMD), which is the most commonly used statistic to examine the balance of covariate distribution between treatment groups.
Journal ArticleDOI
Corticosteroids in IgA Nephropathy: A Retrospective Analysis from the VALIGA Study
Vladimir Tesar,Stéphan Troyanov,Shubha Bellur,Jacobien C. Verhave,H. Terence Cook,John Feehally,Ian S.D. Roberts,Daniel C. Cattran,Rosanna Coppo +8 more
TL;DR: Immunosuppression was associated with a significant reduction in proteinuria, a slower rate of renal function decline, and greater renal survival and CS reduced the risk of progression regardless of initial eGFR and in direct proportion to the extent of proteinuria in this cohort.
Journal ArticleDOI
Association Between Dabigatran vs Warfarin and Risk of Osteoporotic Fractures Among Patients With Nonvalvular Atrial Fibrillation
Wallis C.Y. Lau,Esther W. Chan,Ching-Lung Cheung,Chor-Wing Sing,Kenneth K.C. Man,Gregory Y.H. Lip,Gregory Y.H. Lip,Chung-Wah Siu,Joanne K.Y. Lam,Alan C.H. Lee,Ian C. K. Wong +10 more
TL;DR: Among adults with NVAF receiving anticoagulation, the use of dabigatran compared with warfarin was associated with a lower risk of osteoporotic fracture, and this relationship was statistically significant in patients with a history of falls, fractures, or both.
Journal ArticleDOI
FDA-authorized mRNA COVID-19 vaccines are effective per real-world evidence synthesized across a multi-state health system.
Colin Pawlowski,Patrick Lenehan,Arjun Puranik,Vineet Agarwal,AJ Venkatakrishnan,Michiel J.M. Niesen,John C. O’Horo,Abinash Virk,Melanie D. Swift,Andrew D. Badley,John Halamka,Venky Soundararajan +11 more
TL;DR: In this paper, the authors compared the effectiveness of BNT162b2 and mRNA-1273 in preventing SARS-CoV-2 infection and ICU admission in a cohort of 136,532 individuals.
References
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The central role of the propensity score in observational studies for causal effects
TL;DR: The authors discusses the central role of propensity scores and balancing scores in the analysis of observational studies and shows that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates.
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Matching Methods for Causal Inference: A Review and a Look Forward
TL;DR: A structure for thinking about matching methods and guidance on their use is provided, coalescing the existing research (both old and new) and providing a summary of where the literature on matching methods is now and where it should be headed.
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Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples
TL;DR: Methods to determine the sampling distribution of the standardized difference when the true standardized difference is equal to zero are described, thereby allowing one to determined the range of standardized differences that are plausible with the propensity score model having been correctly specified.
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MatchIt: Nonparametric Preprocessing for Parametric Causal Inference
TL;DR: MatchIt implements a wide range of sophisticated matching methods, making it possible to greatly reduce the dependence of causal inferences on hard-to-justify, but commonly made, statistical modeling assumptions.
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Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation
TL;DR: How to use the techniques of matching, subclassification and/or weighting to help design observational studies is the primary focus of this article, and a new diagnostic table is proposed to aid in this endeavor.