Conference item
The comparative performance of logistic regression and random forest in propensity score methods: A simulation study
- Abstract:
- Propensity scores (PS) are typically estimated using logistic regression (LR). Machine learning techniques such as random forests (RF) have been suggested as promising alternatives for variable selection and PS estimation.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
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(Accepted manuscript, pdf, 96.7KB)
-
- Publisher copy:
- 10.1002/pds.4275
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Authors
Bibliographic Details
- Publisher:
- Wiley Publisher's website
- Journal:
- 33rd International Conference on Pharmacoepidemiology and Therapeutic Risk Management(ICPE 2017) Journal website
- Volume:
- 26
- Issue:
- S2
- Pages:
- 489
- Series:
- 33rd International Conference on Pharmacoepidemiology and Therapeutic Risk Management, Palais des congrès de Montréal, Montréal, Canada, August 26‐30, 2017
- Host title:
- Pharmacoepidemiology and Drug Safety
- Publication date:
- 2017-08-22
- Acceptance date:
- 2017-04-01
- DOI:
- Source identifiers:
-
709988
Item Description
- Pubs id:
-
pubs:709988
- UUID:
-
uuid:3636bc63-91a7-4625-85e6-15f2375745c5
- Local pid:
- pubs:709988
- Deposit date:
- 2018-02-01
Terms of use
- Copyright holder:
- © 2017 Ali, et al Pharmacoepidimeology and Drug Safety © 2017 John Wiley and Sons, Ltd
- Copyright date:
- 2017
- Notes:
- This is the author accepted manuscript following peer review version of the article. The final version is available online from Wiley at: 10.1002/pds.4275
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