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High-dimensional propensity score adjustment in studies of treatment effects using health care claims data

BACKGROUND: Adjusting for large numbers of covariates ascertained from patients’ health care claims data may improve control of confounding, as these variables may collectively be proxies for unobserved factors. Here we develop and test an algorithm that empirically identifies candidate covariates,...

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Autors principals: Schneeweiss, Sebastian, Rassen, Jeremy A., Glynn, Robert J., Avorn, Jerry, Mogun, Helen, Brookhart, M. Alan
Format: Artigo
Idioma:Inglês
Publicat: 2009
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Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC3077219/
https://ncbi.nlm.nih.gov/pubmed/19487948
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1097/EDE.0b013e3181a663cc
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