Dimension reduction and shrinkage methods for high dimensional disease risk scores in historical data

Dimension reduction and shrinkage methods for high dimensional disease risk scores in historical data

Abstract Background Multivariable confounder adjustment in comparative studies of newly marketed drugs can be limited by small numbers of exposed patients and even fewer outcomes. Disease risk scores (DRSs) developed in historical comparator drug users before the new drug entered the market may impr...

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Bibliographic Details
Main Authors: Hiraku Kumamaru, Sebastian Schneeweiss, Robert J. Glynn, Soko Setoguchi, Joshua J. Gagne
Format: Article
Language:English
Published: BMC 2016-04-01
Series:Emerging Themes in Epidemiology
Subjects:
High dimensional propensity score
Disease risk score
Historical data
Shrinkage
Comparative study
Confounding
Online Access:http://link.springer.com/article/10.1186/s12982-016-0047-x

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http://link.springer.com/article/10.1186/s12982-016-0047-x

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