Applied Bayesian modeling and causal inference from incomplete-data perspectives : an essential journey with Donald Rubin's statistical family

By Andrew Gelman, Xiaoli Meng. 2005

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An Extended Class of Instrumental Variables for the Estimation of Causal Effects (2011, background): “Note that here, as in Hirano and Imbens (2004), treatments need not be binary.”
Learning to Personalize from Observational Data (2016, unknown): “20: end if 21: end if output: Personalization model ⌧̂S̃.”
Entropy Balancing for Continuous Treatments (2020, methodology): “Weighting (IPW, Robins, Hernán, and Brumback 2000) – which estimates the GPS using OLS regression similar to Hirano and Imbens (2004) – as well as published balance-optimizing re-weighting algorithms that are readily available in R.”
The (Re)genesis of Values (2015, methodology): “The level of within-strata similarity can be evaluated using a method similar to the one outlined by Hirano and Imbens (2004).”
Comment: Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data. (2008, methodology): “Reviews of causal inference from this perspective are given by Holland (1986), Winship and Sobel (2004), Gelman and Meng (2004) and Rubin (2005).”