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Estimating heterogeneous treatment effects has become increasingly important in many fields and life and death decisions are now based on these estimates: for example, selecting a personalized course of medical treatment.
A doubly robust censoring unbiased transformation
Daniel Rubin and Mark J van der Laan · 2007
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Bayesian nonparametric modeling for causal inference
Jennifer L Hill · 2011
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Multivariate and propensity score matching software with automated balance optimization: The Matching package for R
Jasjeet S. Sekhon · 2011
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Modeling heterogeneous treatment effects in survey experiments with bayesian additive regression trees
Donald P Green and Holger L Kern · 2012
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Bin Yu · 2013
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A simple method for estimating interactions between a treatment and a large number of covariates
Lu Tian, Ash A Alizadeh, Andrew J Gentles, and Robert Tibshirani · 2014
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Machine learning methods for estimating heterogeneous causal effects
Susan Athey and Guido W Imbens · 2015
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Recursive partitioning for heterogeneous causal effects
Susan Athey and Guido W Imbens · 2016
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XGBoost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Bayesian analysis of heterogeneous treatment effects for patient-centered outcomes research
Nicholas C. Henderson, Thomas A. Louis, Chenguang Wang, and Ravi Varadhan · 2016
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A nonparametric bayesian analysis of heterogenous treatment effects in digital experimentation
Matt Taddy, Matt Gardner, Liyun Chen, and David Draper · 2016
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CausalGAM: Estimation of Causal Effects with Generalized Additive Models , 2017
Adam Glynn and Kevin Quinn · 2017
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Meta-learners for estimating heterogeneous treatment effects using machine learning
Learning objectives for treatment effect estimation
Xinkun Nie and Stefan Wager · 2017
Later among the works it cites.
causalToolbox: Toolbox for Causal Inference with emphasize on Heterogeneous Treatment Effect Estimator , 2018
Sören Künzel, Allen Tang, Ling Xie, Theo Saarinen, Peter Bickel, Bin Yu, and Jasjeet Sekhon · 2018
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Transfer learning for estimating causal effects using neural networks
Sören R Künzel, Bradly C Stadie, Nikita Vemuri, Varsha Ramakrishnan, Jasjeet S Sekhon, and Pieter Abbeel · 2018
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Some methods for heterogeneous treatment effect estimation in high dimensions
Scott Powers, Junyang Qian, Kenneth Jung, Alejandro Schuler, Nigam H Shah, Trevor Hastie, and Robert Tibshirani · 2018
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sensitivitymv: Sensitivity Analysis in Observational Studies , 2018
Paul R. Rosenbaum · 2018
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Sören Künzel, Jasjeet Sekhon, Peter Bickel, and Bin Yu · 2017
Cited alongside, same era.
Estimation and inference of heterogeneous treatment effects using random forests
Stefan Wager and Susan Athey
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Estimation and inference of heterogeneous treatment effects using random forests
Stefan Wager and Susan Athey
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Analyzing the modified outcome for heterogeneous treatment effect estimation
Simon Walter, Jasjeet Sekhon, and Bin Yu · 2018
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