Joint sufficient dimension reduction and estimation of conditional and average treatment effects

DOI10.1093/biomet/asx028OpenAlexW2614187857WikidataQ50074275 ScholiaQ50074275MaRDI QIDQ5384495

Ming-Yueh Huang, Kwun Chuen Gary Chan

Publication date: 24 June 2019

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biomet/asx028

zbMATH Keywords

semiparametric efficiencyoptimal bandwidthforward selectionundersmoothinghigh-order kerneljoint central subspace

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

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A Semiparametric Approach to Model Effect Modification ⋮ A Review on Sliced Inverse Regression, Sufficient Dimension Reduction, and Applications ⋮ A beyond multiple robust approach for missing response problem ⋮ Recent advances in statistical methodologies in evaluating program for high-dimensional data ⋮ A Simple and Efficient Estimation of Average Treatment Effects in Models with Unmeasured Confounders ⋮ Statistical inference of heterogeneous treatment effect based on single-index model ⋮ Calibration estimation of semiparametric copula models with data missing at random ⋮ Joint sufficient dimension reduction for estimating continuous treatment effect functions ⋮ Semiparametric double robust and efficient estimation for mean functionals with response missing at random

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