Adjusting for indirectly measured confounding using large-scale propensity score.

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作者： Linying,Zhang ^[1] ; Yixin,Wang ^[2] ; Martijn J,Schuemie ^[3] ; David M,Blei ^[4] ; George,Hripcsak ^[5]

作者单位： Department of Biomedical Informatics, Columbia University Irving Medical Center, 622 W. 168th Street, PH20, New York, 10032, NY, USA. ^[1] Department of Statistics, University of Michigan, 1085 S University Ave, Ann Arbor, 48109, MI, USA. ^[2] Janssen Research and Development, 1125 Trenton-Harbourton Road, Titusville, 08560, NJ, USA. ^[3] Department of Statistics, Columbia University, 1255 Amsterdam Ave, New York, 10027, NY, USA; Department of Computer Science, Columbia University, 500 West 120 Street, Room 450 MC0401, New York, 10027, NY, USA. ^[4] Department of Biomedical Informatics, Columbia University Irving Medical Center, 622 W. 168th Street, PH20, New York, 10032, NY, USA; Medical Informatics Services, New York-Presbyterian Hospital, 622 W. 168th Street, PH20, New York, 10032, NY, USA. Electronic address: hripcsak@columbia.edu. ^[5]

关键词 Causal inference Electronic health record Observational study Propensity score Unmeasured confounder

主题词因果律(Causality);倾向性评分(Propensity Score)

DOI 10.1016/j.jbi.2022.104204

PMID 36108816

发布时间 2024-09-08

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