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Metalearners for estimating heterogeneous treatment effects using machine learning
There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of metaalgorithms that can take advantage of any supervised learning or regression method in machine learning and statistics to estimate the condition...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
National Academy of Sciences
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410831/ https://www.ncbi.nlm.nih.gov/pubmed/30770453 http://dx.doi.org/10.1073/pnas.1804597116 |