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- W4311565529 abstract "This paper addresses the problem of estimating causal effects when adjustment variables in the back-door or front-door criterion are partially observed. For such scenarios, we derive bounds on the causal effects by solving two non-linear optimization problems, and demonstrate that the bounds are sufficient. Using this optimization method, we propose a framework for dimensionality reduction that allows one to trade bias for estimation power, and demonstrate its performance using simulation studies." @default.
- W4311565529 created "2022-12-27" @default.
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- W4311565529 date "2021-06-22" @default.
- W4311565529 modified "2023-09-26" @default.
- W4311565529 title "Bounds on Causal Effects and Application to High Dimensional Data" @default.
- W4311565529 doi "https://doi.org/10.48550/arxiv.2106.12121" @default.
- W4311565529 hasPublicationYear "2021" @default.
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