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...

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Detalles Bibliográficos
Autores principales: Le Borgne, Florent, Chatton, Arthur, Léger, Maxime, Lenain, Rémi, Foucher, Yohann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
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

Internet

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

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