G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes
Abstract 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 misspecifi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-81110-0 |