CALM learns embeddings to align mismatched covariates between RCTs and observational studies, transfers outcome models, and calibrates them on trial data to improve CATE estimation without imputation.
Understand- ing the risks and rewards of combining unbiased and possibly biased estimators, with applications to causal inference.arXiv preprint arXiv:2205.10467
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A review organizes externally controlled trial methodology through causal estimands and identifiability assumptions for single-arm and hybrid designs with borrowing strategies.
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Improving RCT-Based CATE Estimation Under Covariate Mismatch via Calibrated Alignment
CALM learns embeddings to align mismatched covariates between RCTs and observational studies, transfers outcome models, and calibrates them on trial data to improve CATE estimation without imputation.
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Externally Controlled Trials: A Review of Design and Borrowing Through a Causal Lens
A review organizes externally controlled trial methodology through causal estimands and identifiability assumptions for single-arm and hybrid designs with borrowing strategies.