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G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes
In clinical research, there is a growing interest in the use of propensity score-based methods to estimate causal effects. G-computation is an alternative because of its high statistical power. Machine learning is also increasingly used because of its possible robustness to model misspecification. I...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809122/ https://www.ncbi.nlm.nih.gov/pubmed/33446866 http://dx.doi.org/10.1038/s41598-021-81110-0 |