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2013 Estimating multiple treatment effects using two-phase semiparametric regression estimators
Cindy Yu, Jason Legg, Bin Liu
Electron. J. Statist. 7: 2737-2761 (2013). DOI: 10.1214/13-EJS856

Abstract

We propose a semiparametric two-phase regression estimator with a semiparametric generalized propensity score estimator for estimating average treatment effects in the presence of the first-phase sampling. The proposed estimator can be easily extended to any number of treatments and does not rely on a prespecified form of the response or outcome functions. The proposed estimator is shown to reduce bias found in standard estimators that ignore the first-phase sample design, and can have improved efficiency compared to the inverse propensity weighted estimators. Results from simulation studies and from an empirical study of NHANES are presented.

Citation

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Cindy Yu. Jason Legg. Bin Liu. "Estimating multiple treatment effects using two-phase semiparametric regression estimators." Electron. J. Statist. 7 2737 - 2761, 2013. https://doi.org/10.1214/13-EJS856

Information

Published: 2013
First available in Project Euclid: 18 November 2013

zbMATH: 1283.62089
MathSciNet: MR3138836
Digital Object Identifier: 10.1214/13-EJS856

Rights: Copyright © 2013 The Institute of Mathematical Statistics and the Bernoulli Society

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