Health status balancing weights for estimation of health care disparities
Author:
Funder
National Cancer Institute
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health,Health Policy
Link
https://link.springer.com/content/pdf/10.1007/s10742-022-00287-7.pdf
Reference26 articles.
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3. Choi, B.Y., Wang, C.-P., Michalek, J., Gelfond, J.: Power comparison for propensity score methods. Comput Stat. 34, 743–761 (2019). https://doi.org/10.1007/s00180-018-0852-5
4. Choi, B.Y., Wang, C., Gelfond, J.: Machine learning outcome regression improves doubly robust estimation of average causal effects. Pharmacoepidemiol. Drug Saf. 29, 1120–1133 (2020). https://doi.org/10.1002/pds.5074
5. Cook, B.L., McGuire, T.G., Meara, E., Zaslavsky, A.M.: Adjusting for health status in non-linear models of health care disparities. Health Serv Outcomes Res Methodol. 9, 1–21 (2009). https://doi.org/10.1007/s10742-008-0039-6
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