How unmeasured confounding in a competing risks setting can affect treatment effect estimates in observational studies
(2019)
Journal Article
Barrowman, M. A., Peek, N., Lambie, M., Martin, G. P., & Sperrin, M. (2019). How unmeasured confounding in a competing risks setting can affect treatment effect estimates in observational studies. BMC medical research methodology, 19, Article 166. https://doi.org/10.1186/s12874-019-0808-7
Background
Analysis of competing risks is commonly achieved through a cause specific or a subdistribution framework using Cox or Fine & Gray models, respectively. The estimation of treatment effects in observational data is prone to unmeasured confo...
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