Confounder Data Management
Confounder Data Management is a data management framework designed to identify, assess, and mitigate the influence of confounding variables in observational and experimental studies to ensure valid causal inferences.
9
Publications
303
Citations
47
Authors
28
Institutions
Publications per year
2017–2026
5
Parents
9
Controlling Confounding When Studying Large Pharmacoepidemiologic Databases
Jean‐Paul Collet, Douglas E. Schaubel, James Hanley et al. · Epidemiology · 1998 · 37 citations
Sengwee Toh, Luis A. Garcı́a Rodrı́guez, Miguel A. Hernán · Pharmacoepidemiology and Drug Safety · 2012 · 33 citations · Full text
Public Health, Pharmacology, Comparative Effectiveness Research +13
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47
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h-index
2
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2
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1–5 of 47
28
Harvard University
Cambridge, United States
3 h-index
11 publications
314 citations

Brigham and Women's Hospital
Boston, United States
2 h-index
9 publications
248 citations
Stanford University
Stanford, United States
2 h-index
10 publications
365 citations

Jewish General Hospital
Montreal, Canada
1 h-index
2 publications
74 citations
Massachusetts Institute of Technology
Cambridge, United States
1 h-index
1 publications
33 citations
German Centre for Cardiovascular Research
Berlin, Germany
1 h-index
1 publications
37 citations
Centro Español de Investigación Farmacoepidemiológica
Madrid, Spain
1 h-index
1 publications
33 citations
European Molecular Biology Laboratory
Hamburg, Germany
1 h-index
3 publications
111 citations
1–8 of 28
2 publications · 61 citations
2
h-index
1 publications · 38 citations
1
h-index
1 publications · 37 citations
1
h-index
1 publications · 37 citations
1
h-index
1 publications · 27 citations
1
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1–5