Journal article icon

Journal article

Modeling time-varying exposure using inverse probability of treatment weights

Abstract:

For estimating the causal effect of treatment exposure on the occurrence of adverse events, inverse pro bability weights (IPW) can be used in marginal structural models to correct for time-dependent confounding. The R package ipw allows IPW estimation by modeling the relationship between the exposure and confounders via several regression models, among which is the Cox model. For right-censored data and time-dependent exposures such as treatment switches, the ipw package allows a singl...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Publisher copy:
10.1002/bimj.201600223

Authors


More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM; Tropical Medicine
Role:
Author
More from this funder
Name:
French National Agency for Medicines and Health Products Safety
Publisher:
Wiley
Journal:
Biometrical Journal More from this journal
Volume:
60
Issue:
2
Pages:
323-332
Publication date:
2017-12-17
Acceptance date:
2017-10-30
DOI:
EISSN:
1521-4036
ISSN:
0323-3847
Keywords:
Pubs id:
pubs:829605
UUID:
uuid:8c5c3021-4975-473d-83d6-9fa120702124
Local pid:
pubs:829605
Source identifiers:
829605
Deposit date:
2018-03-16

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP