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Model-free approach to quantifying the proportion of treatment effect explained by a surrogate marker
In randomized clinical trials, the primary outcome, Y, often requires long-term follow-up and/or is costly to measure. For such settings, it is desirable to use a surrogate marker, S, to infer the treatment effect on Y, Δ. Identifying such an S and quantifying the proportion of treatment effect on Y...
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| Publicado no: | Biometrika |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7315285/ https://ncbi.nlm.nih.gov/pubmed/32587413 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/biomet/asz065 |
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