Conditional generative adversarial networks for individualized causal mediation analysis
Most classical methods popularly used in causal mediation analysis can only estimate the average causal effects and are difficult to apply to precision medicine. Although identifying heterogeneous causal effects has received some attention, the causal effects are explored using the assumptive parame...
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| Main Authors: | , , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
De Gruyter
2024-05-01
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| Series: | Journal of Causal Inference |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jci-2022-0069 |
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