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On Causal Inferences for Personalized Medicine: How Hidden Causal Assumptions Led to Erroneous Causal Claims About the D-Value
Personalized medicine asks if a new treatment will help a particular patient, rather than if it improves the average response in a population. Without a causal model to distinguish these questions, interpretational mistakes arise. These mistakes are seen in an article by Demidenko [2016] that recomm...
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| 出版年: | Am Stat |
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| 主要な著者: | , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7821975/ https://ncbi.nlm.nih.gov/pubmed/33487634 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/00031305.2019.1575771 |
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