Comment on "How pharmacoepidemiology networks can manage distributed analyses to improve replicability and transparency and minimize bias"
Pharmacoepidemiol Drug Saf
.
2019 Jul;28(7):1032-1033.
doi: 10.1002/pds.4798.
Epub 2019 May 8.
Authors
Martijn J Schuemie
1
2
3
,
David Madigan
1
4
,
Patrick B Ryan
1
2
5
,
Christian Reich
1
6
,
Marc A Suchard
1
3
7
8
,
Jesse A Berlin
1
2
,
George Hripcsak
1
5
9
Affiliations
1
Observational Health Data Sciences and Informatics, New York, NY.
2
Epidemiology Analytics, Janssen Research and Development, Titusville, NJ.
3
Department of Biostatistics, University of California, Los Angeles, CA.
4
Department of Statistics, Columbia University, New York, NY.
5
Department of Biomedical Informatics, Columbia University Medical Center, New York, NY.
6
Real World Analytics Solutions, IQVIA, Cambridge, MA.
7
Department of Biomathematics, University of California, Los Angeles, CA.
8
Department of Human Genetics, University of California, Los Angeles, CA.
9
Medical Informatics Services, New York-Presbyterian Hospital, New York, NY.
PMID:
31066478
DOI:
10.1002/pds.4798
No abstract available
Publication types
Letter
Comment
MeSH terms
Bias
Pharmacoepidemiology*
Grants and funding
R01 LM006910/LM/NLM NIH HHS/United States