Semiparametric methods for estimation of a nonlinear exposure-outcome relationship using instrumental variables with application to Mendelian randomization-Reference-Cited by-同舟云学术

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Semiparametric methods for estimation of a nonlinear exposure-outcome relationship using instrumental variables with application to Mendelian randomization

Published:2017-03-20 Issue:4 Volume:41 Page:341-352
ISSN:0741-0395
Container-title:Genetic Epidemiology
language:en
Short-container-title:Genet. Epidemiol.

Author:

Staley James R.¹,Burgess Stephen¹^ORCID

Affiliation:

1. Strangeways Research Laboratory, Department of Public Health and Primary Care, Cardiovascular Epidemiology Unit; University of Cambridge; United Kingdom

Funder

Medical Research Council

Pfizer

British Heart Foundation

UK National Institute for Health Research Cambridge Biomedical Research Centre

European Research Council

European Commission Framework Programme 7

Wellcome Trust

Publisher

Wiley

Subject

Genetics (clinical),Epidemiology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/gepi.22041/fullpdf

Reference32 articles.

1. An integrated map of genetic variation from 1,092 human genomes;Abecasis;Nature,2012

2. Identification of causal effects using instrumental variables;Angrist;Journal of the American Statistical Association,1996

3. Flexible meta-regression functions for modeling aggregate dose-response data, with an application to alcohol and mortality;Bagnardi;American Journal of Epidemiology,2004

4. Mendelian randomization analysis with multiple genetic variants using summarized data;Burgess;Genetic Epidemiology,2013

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