Multiple robustness estimation in causal inference
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Publication:5077930
DOI10.1080/03610926.2018.1520881OpenAlexW2903014606WikidataQ128824499 ScholiaQ128824499MaRDI QIDQ5077930
Publication date: 20 May 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2018.1520881
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Cites Work
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- Doubly Robust Estimation in Missing Data and Causal Inference Models
- Empirical likelihood on the full parameter space
- Empirical likelihood and general estimating equations
- Calibration of the empirical likelihood method for a vector mean
- Semiparametric theory and missing data.
- On the robustness of empirical likelihood ratio confidence intervals for location
- Bounded, efficient and doubly robust estimation with inverse weighting
- Semiparametric inverse propensity weighting for nonignorable missing data
- Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data
- The central role of the propensity score in observational studies for causal effects
- Empirical likelihood ratio confidence intervals for a single functional
- Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
- On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
- Using empirical likelihood methods to obtain range restricted weights in regression estimators for surveys
- Multiply Robust Estimation in Regression Analysis With Missing Data
- Empirical-Likelihood-Based Inference in Missing Response Problems and Its Application in Observational Studies
- Estimation with missing data: beyond double robustness
- Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
- A Generalization of Sampling Without Replacement From a Finite Universe
- Maximum Likelihood Estimation of Misspecified Models
