Generalized estimating equations for genome-wide association studies using longitudinal phenotype data

Author:

Sitlani Colleen M.1,Rice Kenneth M.2,Lumley Thomas3,McKnight Barbara2,Cupples L. Adrienne4,Avery Christy L.5,Noordam Raymond67,Stricker Bruno H. C.7,Whitsel Eric A.8,Psaty Bruce M.910

Affiliation:

1. Department of Medicine; University of Washington; Seattle WA U.S.A.

2. Department of Biostatistics; University of Washington; Seattle WA U.S.A

3. Department of Statistics; University of Auckland; Auckland New Zealand

4. Department of Biostatistics; Boston University; Boston MA U.S.A.

5. Department of Epidemiology; University of North Carolina; Chapel Hill NC U.S.A.

6. Department of Internal Medicine; Erasmus Medical Center; Rotterdam NL U.S.A.

7. Department of Epidemiology; Erasmus Medical Center; Rotterdam The Netherlands

8. Departments of Epidemiology and Medicine; University of North Carolina; Chapel Hill NC U.S.A.

9. Departments of Medicine, Epidemiology, and Health Services; University of Washington; Seattle WA U.S.A.

10. Group Health Research Institute; Group Health Cooperative; Seattle WA U.S.A.

Funder

National Institutes of Health

National Heart, Lung, and Blood Institute

National Human Genome Research Institute

National Institute on Aging

National Center for Research Resources

National Center for Advancing Translational Sciences

National Institute of Diabetes and Digestive and Kidney Diseases

Netherlands Organisation for Health Research and Development

European Commission

Municipality of Rotterdam

Netherlands Ministry for Health, Welfare and Sports

Netherlands Ministry of Education, Culture and Science

Netherlands Organisation for Scientific Research NWO

Netherlands Research Institute for Diseases in the Elderly (RIDE)

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Reference47 articles.

1. Drug-gene interactions and the search for missing heritability: a cross-sectional pharmacogenomics study of the QT interval;Avery;The Pharmacogenomics Journal,2013

2. Rare variant association analysis methods for complex traits;Asimit;Annual Review of Genetics,2010

3. Cohorts for heart and aging research in genomic epidemiology (CHARGE) consortium: design of prospective meta-analyses of genome-wide association studies from five cohorts;Psaty;Circulation: Cardiovascular Genetics,2009

4. The Cardiovascular Health Study: design and rationale;Fried;Annals of Epidemiology,1991

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