Entropy balancing for causal generalization with target sample summary information
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Publication:6589264
DOI10.1111/biom.13825zbMATH Open1543.62587MaRDI QIDQ6589264
Menggang Yu, Guanhua Chen, Rui Chen
Publication date: 19 August 2024
Published in: Biometrics (Search for Journal in Brave)
Cites Work
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- Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data
- The central role of the propensity score in observational studies for causal effects
- On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
- Outcome‐adaptive lasso: Variable selection for causal inference
- Robust Estimation of Encouragement Design Intervention Effects Transported Across Sites
- Building Representative Matched Samples With Multi-Valued Treatments in Large Observational Studies
- Doubly Robust Inference when Combining Probability and Non-Probability Samples with High Dimensional Data
- Rerandomization and Regression Adjustment
- Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations
- Globally Efficient Non-Parametric Inference of Average Treatment Effects by Empirical Balancing Calibration Weighting
- Kernel-based covariate functional balancing for observational studies
- Covariate Balancing Propensity Score
- Extending inferences from a randomized trial to a new target population
- Balancing vs modeling approaches to weighting in practice
- From sample average treatment effect to population average treatment effect on the treated: combining experimental with observational studies to estimate population treatment effects
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