On a preference-based instrumental variable approach in reducing unmeasured confounding-by-indication-Reference-Cited by-同舟云学术

On a preference-based instrumental variable approach in reducing unmeasured confounding-by-indication

Published:2014-12-29 Issue:7 Volume:34 Page:1150-1168
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

Li Yun¹²^ORCID,Lee Yoonseok³,Wolfe Robert A.²,Morgenstern Hal²⁴,Zhang Jinyao²,Port Friedrich K.²,Robinson Bruce M.²⁵

Affiliation:

1. Department of Biostatistics, School of Public Health; University of Michigan; Ann Arbor MI 48109 U.S.A.

2. Arbor Research Collaborative for Health; Ann Arbor MI 48104 U.S.A.

3. Department of Economics and Center for Policy Research, Maxwell School of Citizenship and Public Affairs; Syracuse University; Syracuse NY 13244 U.S.A.

4. Departments of Epidemiology, Environmental Health Sciences, and Urology; University of Michigan; Ann Arbor MI 48109 U.S.A.

5. Department of Medicine; University of Michigan; Ann Arbor MI 48109 U.S.A.

Funder

Amgen, Kyowa Hakko Kirin, Saofi Renal, Abbott, Baxter, Vifor Fresenius Renal Pharma

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Reference52 articles.

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4. Instrumental variable methods for causal inference;Baiocchi;Statistics in Medicine,2014

5. Preference-based instrumental variable methods for the estimation of treatment effects: assessing validity and interpreting results;Brookhart;The International Journal of Biostatistics,2007

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