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Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models
Longitudinal observational data on patients can be used to investigate causal effects of time‐varying treatments on time‐to‐event outcomes. Several methods have been developed for estimating such effects by controlling for the time‐dependent confounding that typically occurs. The most commonly used...
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| Pubblicato in: | Stat Med |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
John Wiley & Sons, Inc.
2023
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7614580/ https://ncbi.nlm.nih.gov/pubmed/37086186 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.9718 |
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