The International Journal of Biostatistics Empirical Efficiency Maximization : Improved Locally Efficient Covariate Adjustment in Randomized Experiments and Survival Analysis
By Donald B. Rubin. 2011
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Masatoshi Uehara
- Nathan Kallus
- Ziyang Tang
- Nan Jiang
- Susan Athey
- Andrew Bennett
- Stefan Wager
- Jack Dunn
Citations in the corpus
- Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning (2019, background): “2, [4, 6, 26] further suggest that to pick τ̂ to minimize an estimate of the asymptotic variance of β̂d({q(x, a; τ)}T−1 t=0 ), leading to the MDR estimator [6] for OPE.”
- Bounded, efficient and doubly robust estimation with inverse weighting (2010, unknown): “…if the propensity score model is correctly specified, then they are asymptotically at least as efficient as the augmented inverse-probability-weighted estimator that uses the true propensity score and an optimally fitted outcome regression function (Rubin & van der Laan, 2008; Tan, 2008).”
- Combining Inverse Probability Weighting and Multiple Imputation to Improve Robustness of Estimation (2016, background): “W Iˇ/ j Zº (e.g. Rubin and van der Laan, 2008).”