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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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Bibliographic Details
Main Authors: Schneeweiss, Sebastian, Rassen, Jeremy A., Glynn, Robert J., Avorn, Jerry, Mogun, Helen, Brookhart, M. Alan
Format: Artigo
Language:Inglês
Published: 2009
Subjects:
Online Access: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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