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Simulating longitudinal data from marginal structural models using the additive hazard model [Image: see text]
Observational longitudinal data on treatments and covariates are increasingly used to investigate treatment effects, but are often subject to time-dependent confounding. Marginal structural models (MSMs), estimated using inverse probability of treatment weighting or the g-formula, are popular for ha...
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| Veröffentlicht in: | Biom J |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2021
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7612178/ https://ncbi.nlm.nih.gov/pubmed/33983641 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/bimj.202000040 |
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