A causal roadmap for generating high-quality real-world evidence

Dang, L. E., Gruber, S., Lee, H., Dahabreh, I. J., Stuart, E. A., Williamson, B. D., Wyss, R., Díaz, I., Ghosh, D., Kıcıman, E., Alemayehu, D., Hoffman, K. L., Vossen, C. Y., Huml, R. A., Ravn, H., Kvist, K., Pratley, R., Shih, M.-C., Pennello, G., … Petersen, M. (2023). A causal roadmap for generating high-quality real-world evidence. Journal of Clinical and Translational Science, 7(1). https://doi.org/10.1017/cts.2023.635
Authors:
Lauren E Dang
Susan Gruber
Hana Lee
Issa J Dahabreh
Elizabeth A Stuart
Brian D Williamson
Richard Wyss
Iván Díaz
Debashis Ghosh
Emre Kıcıman
Demissie Alemayehu
Katherine L Hoffman
Carla Y Vossen
Raymond A Huml
Henrik Ravn
Kajsa Kvist
Richard Pratley
Mei-Chiung Shih
Gene Pennello
David Martin
Salina P Waddy
Charles E Barr
Mouna Akacha
John B Buse
Mark van der Laan
Maya Petersen
Affiliated Authors:
Katherine L Hoffman
Author Keywords:
causal inference
estimands
machine learning
real-world evidence
sensitivity analysis
simulations
Publication Type:
Article
Unique ID:
10.1017/cts.2023.635
PMID:
Publication Date:
Data Source:
PubMed

Record Created: