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Bayesian Statistics 9$
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José M. Bernardo, M. J. Bayarri, James O. Berger, A. P. Dawid, David Heckerman, Adrian F. M. Smith, and Mike West

Print publication date: 2011

Print ISBN-13: 9780199694587

Published to Oxford Scholarship Online: January 2012

DOI: 10.1093/acprof:oso/9780199694587.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 14 May 2021

Bayesian Methods in Pharmacovigilance *

Bayesian Methods in Pharmacovigilance *

(p.421) Bayesian Methods in Pharmacovigilance*
Bayesian Statistics 9

David Madigan

Patrick Ryan

Shawn Simpson

Ivan Zorych

Oxford University Press

Regulators such as the U.S. Food and Drug Administration have elaborate, multi‐year processes for approving new drugs as safe and effective. Nonetheless, in recent years, several approved drugs have been withdrawn from the market because of serious and sometimes fatal side effects. We describe statistical methods for post‐approval data analysis that attempt to detect drug safety problems as quickly as possible. Bayesian approaches are especially useful because of the high dimensionality of the data, and, in the future, for incorporating disparate sources of information.

Keywords:   Drug safety, Shrinkage, High‐dimensional modeling, Poisson regression

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