Comparing Two Proxy Methods for Causal Identification
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913108927184896 |
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| author | Guo, Helen Ogburn, Elizabeth L. Shpitser, Ilya |
| author_facet | Guo, Helen Ogburn, Elizabeth L. Shpitser, Ilya |
| contents | Identifying causal effects in the presence of unmeasured variables is a fundamental challenge in causal inference, for which proxy variable methods have emerged as a powerful solution. We contrast two major approaches in this framework: (1) bridge equation methods, which leverage solutions to integral equations to recover causal targets, and (2) array decomposition methods, which recover latent factors used to identify counterfactual quantities via eigendecomposition tasks. We compare the model restrictions underlying these two approaches and provide insight into implications of the underlying assumptions, clarifying the scope of applicability for each method. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2512_00175 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Comparing Two Proxy Methods for Causal Identification Guo, Helen Ogburn, Elizabeth L. Shpitser, Ilya Methodology Machine Learning Identifying causal effects in the presence of unmeasured variables is a fundamental challenge in causal inference, for which proxy variable methods have emerged as a powerful solution. We contrast two major approaches in this framework: (1) bridge equation methods, which leverage solutions to integral equations to recover causal targets, and (2) array decomposition methods, which recover latent factors used to identify counterfactual quantities via eigendecomposition tasks. We compare the model restrictions underlying these two approaches and provide insight into implications of the underlying assumptions, clarifying the scope of applicability for each method. |
| title | Comparing Two Proxy Methods for Causal Identification |
| topic | Methodology Machine Learning |
| url | https://arxiv.org/abs/2512.00175 |