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The idea of covariate balance is at the core of causal inference.
‘‘On the application of probability theory to agricultural experiments. Essay on principles. Section 9’’
Jerzy Neyman · 1923
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‘‘On the application of probability theory to agricultural experiments. Essay on principles. Section 9’’
Jerzy Neyman · 1923
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W Deming and Frederick Stephan · 1940
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‘‘On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known’’
W Deming and Frederick Stephan · 1940
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‘‘The planning of observational studies of human populations’’
W.. Cochran · 1965
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‘‘The planning of observational studies of human populations’’
W.. Cochran · 1965
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‘‘Estimating causal effects of treatments in randomized and nonrandomized studies’’
Donald Rubin · 1974
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‘‘Estimating causal effects of treatments in randomized and nonrandomized studies’’
Donald Rubin · 1974
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‘‘Comment on ‘‘Randomization Analysis of Experimental Data: The Fisher Randomization Test"’’
Donald Rubin · 1980
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‘‘Comment on ‘‘Randomization Analysis of Experimental Data: The Fisher Randomization Test"’’
Donald Rubin · 1980
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‘‘The Central Role of the Propensity Score in Observational Studies for Causal Effects’’
Paul Rosenbaum and Donald Rubin · 1983
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‘‘The Central Role of the Propensity Score in Observational Studies for Causal Effects’’
Paul Rosenbaum and Donald Rubin · 1983
Earlier work this paper cites.
‘‘Constructing a control group using multivariate matched sampling methods that incorporate the propensity score’’
P.. Rosenbaum and D.. Rubin · 1985
Earlier work this paper cites.
‘‘Constructing a control group using multivariate matched sampling methods that incorporate the propensity score’’
P.. Rosenbaum and D.. Rubin · 1985
Earlier work this paper cites.
‘‘On asymptotically efficient estimation in semiparametric models’’
Anton Schick · 1986
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‘‘On asymptotically efficient estimation in semiparametric models’’
Anton Schick · 1986
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‘‘Model-based direct adjustment’’
Paul Rosenbaum · 1987
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‘‘Model-based direct adjustment’’
Paul Rosenbaum · 1987
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‘‘On differentiable functionals’’
Aad van Vaart · 1991
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‘‘On differentiable functionals’’
Aad van Vaart · 1991
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‘‘Calibration estimators in survey sampling’’
Jean-Claude Deville and Carl-Erik Särndal · 1992
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‘‘Calibration estimators in survey sampling’’
Jean-Claude Deville and Carl-Erik Särndal · 1992
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‘‘Estimation of regression coefficients when some regressors are not always observed’’
James Robins, Andrea Rotnitzky and Lue Zhao · 1994
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‘‘Estimation of regression coefficients when some regressors are not always observed’’
James Robins, Andrea Rotnitzky and Lue Zhao · 1994
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‘‘Weak convergence’’
Aad van Vaart and Jon Wellner · 1996
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‘‘Weak convergence’’
Aad van Vaart and Jon Wellner · 1996
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‘‘Asymptotic statistics’’
Aad van Vaart · 2000
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‘‘Asymptotic statistics’’
Aad van Vaart · 2000
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‘‘Convex optimization’’
Stephen Boyd and Lieven Vandenberghe · 2004
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‘‘Nonparametric estimation of average treatment effects under exogeneity: A review’’
Guido Imbens · 2004
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‘‘Convex optimization’’
Stephen Boyd and Lieven Vandenberghe · 2004
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‘‘Nonparametric estimation of average treatment effects under exogeneity: A review’’
Guido Imbens · 2004
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‘‘Large sample properties of matching estimators for average treatment effects’’
Alberto Abadie and Guido Imbens · 2006
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‘‘Sobolev spaces associated to the harmonic oscillator’’
Bruno Bongioanni and José Torrea · 2006
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‘‘Large sample properties of matching estimators for average treatment effects’’
Alberto Abadie and Guido Imbens · 2006
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‘‘Sobolev spaces associated to the harmonic oscillator’’
Bruno Bongioanni and José Torrea · 2006
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‘‘Learning theory: an approximation theory viewpoint’’
Felipe Cucker and Ding Zhou · 2007
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‘‘Bracketing metric entropy rates and empirical central limit theorems for function classes of Besov-and Sobolev-type’’
Richard Nickl and Benedikt Pötscher · 2007
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‘‘Minimum distance matched sampling with fine balance in an observational study of treatment for ovarian cancer’’
P.. Rosenbaum, R.. Ross and J.. Silber · 2007
Earlier work this paper cites.
‘‘Bracketing metric entropy rates and empirical central limit theorems for function classes of Besov-and Sobolev-type’’
Richard Nickl and Benedikt Pötscher · 2007
Earlier work this paper cites.
‘‘Learning theory: an approximation theory viewpoint’’
Felipe Cucker and Ding Zhou · 2007
Earlier work this paper cites.
‘‘Bracketing metric entropy rates and empirical central limit theorems for function classes of Besov-and Sobolev-type’’
Richard Nickl and Benedikt Pötscher · 2007
Earlier work this paper cites.
‘‘Minimum distance matched sampling with fine balance in an observational study of treatment for ovarian cancer’’
P.. Rosenbaum, R.. Ross and J.. Silber · 2007
Earlier work this paper cites.
‘‘Bracketing metric entropy rates and empirical central limit theorems for function classes of Besov-and Sobolev-type’’
Richard Nickl and Benedikt Pötscher · 2007
Earlier work this paper cites.
‘‘Semiparametric minimax rates’’
James Robins, Eric Tchetgen, Lingling Li and Aad van Vaart · 2009
Earlier work this paper cites.
‘‘Semiparametric minimax rates’’
James Robins, Eric Tchetgen, Lingling Li and Aad van Vaart · 2009
Earlier work this paper cites.
‘‘Cross-validated targeted minimum-loss-based estimation’’
Wenjing Zheng and Mark van Laan · 2011
Earlier work this paper cites.
‘‘Cross-validated targeted minimum-loss-based estimation’’
Wenjing Zheng and Mark van Laan · 2011
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‘‘Inverse probability tilting for moment condition models with missing data’’
Bryan Graham, Cristine de Xavier and Daniel Egel · 2012
Earlier work this paper cites.
‘‘Entropy balancing for causal effects: a multivariate reweighting method to produce balanced samples in observational studies’’
Jens Hainmueller · 2012
Earlier work this paper cites.
‘‘An introduction to Banach space theory’’
Robert Megginson · 2012
Earlier work this paper cites.
‘‘Inverse probability tilting for moment condition models with missing data’’
Bryan Graham, Cristine de Xavier and Daniel Egel · 2012
Cited alongside, same era.
‘‘Entropy balancing for causal effects: a multivariate reweighting method to produce balanced samples in observational studies’’
Jens Hainmueller · 2012
Cited alongside, same era.
‘‘An introduction to Banach space theory’’
Robert Megginson · 2012
Cited alongside, same era.
‘‘Assumptionless consistency of the lasso’’
Sourav Chatterjee · 2013
Cited alongside, same era.
‘‘Assumptionless consistency of the lasso’’
Sourav Chatterjee · 2013
Cited alongside, same era.
‘‘Augmented minimax linear estimation’’
David Hirshberg and Stefan Wager · 2018
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‘‘Balancing covariates via propensity score weighting’’
Fan Li, Kari Morgan and Alan Zaslavsky · 2018
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‘‘Cross-fitting and fast remainder rates for semiparametric estimation’’
Whitney Newey and James Robins · 2018
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‘‘High-dimensional probability: An introduction with applications in data science’’
Roman Vershynin · 2018
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‘‘Kernel-based covariate functional balancing for observational studies’’
Raymond Wong and Kwun Chan · 2018
Later among the works it cites.
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Kosuke Imai and Marc Ratkovic · 2014
Cited alongside, same era.
‘‘Martingale limit theory and its application’’
Peter Hall and Christopher Heyde · 2014
Cited alongside, same era.
‘‘Covariate balancing propensity score’’
Kosuke Imai and Marc Ratkovic · 2014
Cited alongside, same era.
‘‘Martingale limit theory and its application’’
Peter Hall and Christopher Heyde · 2014
Cited alongside, same era.
‘‘Convex optimization in normed spaces: theory, methods and examples’’
Juan Peypouquet · 2015
Cited alongside, same era.
‘‘Stable weights that balance covariates for estimation with incomplete outcome data’’
J.. Zubizarreta · 2015
Cited alongside, same era.
‘‘Approximation of mixed order Sobolev functions on the d-torus: asymptotics, preasymptotics, and d-dependence’’
Thomas Kühn, Winfried Sickel and Tino Ullrich · 2015
Cited alongside, same era.
‘‘Approximate residual balancing: debiased inference of average treatment effects in high dimensions’’
Susan Athey, Guido Imbens and Stefan Wager · 2018
Later among the works it cites.
‘‘Augmented minimax linear estimation’’
David Hirshberg and Stefan Wager · 2018
Later among the works it cites.
‘‘Kernel-based covariate functional balancing for observational studies’’
Raymond Wong and Kwun Chan · 2018
Later among the works it cites.
‘‘Minimax semiparametric learning with approximate sparsity’’
Jelena Bradic, Victor Chernozhukov, Whitney Newey and Yinchu Zhu · 2019
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‘‘Sparsity double robust inference of average treatment effects’’
Jelena Bradic, Stefan Wager and Yinchu Zhu · 2019
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‘‘Minimax linear estimation of the retargeted mean’’
David Hirshberg, Arian Maleki and J.. Zubizarreta · 2019
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‘‘De-biased machine learning in instrumental variable models for treatment effects’’
Rahul Singh and Liyang Sun · 2019
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‘‘Covariate balancing propensity score by tailored loss functions’’
Qingyuan Zhao · 2019
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Aurélien Bibaut and Mark van Laan · 2019
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‘‘Minimax linear estimation of the retargeted mean’’
David Hirshberg, Arian Maleki and J.. Zubizarreta · 2019
Later among the works it cites.
‘‘Minimax semiparametric learning with approximate sparsity’’
Jelena Bradic, Victor Chernozhukov, Whitney Newey and Yinchu Zhu · 2019
Later among the works it cites.
‘‘Sparsity double robust inference of average treatment effects’’
Jelena Bradic, Stefan Wager and Yinchu Zhu · 2019
Later among the works it cites.
‘‘Minimax linear estimation of the retargeted mean’’
David Hirshberg, Arian Maleki and J.. Zubizarreta · 2019
Later among the works it cites.
‘‘De-biased machine learning in instrumental variable models for treatment effects’’
Rahul Singh and Liyang Sun · 2019
Later among the works it cites.
‘‘Covariate balancing propensity score by tailored loss functions’’
Qingyuan Zhao · 2019
Later among the works it cites.
Aurélien Bibaut and Mark van Laan · 2019
Later among the works it cites.
‘‘Minimax linear estimation of the retargeted mean’’
David Hirshberg, Arian Maleki and J.. Zubizarreta · 2019
Later among the works it cites.
‘‘Kernel Balancing: A flexible non-parametric weighting procedure for estimating causal effects’’
Chad Hazlett · 2020
Later among the works it cites.
‘‘Generalized optimal matching methods for causal inference’’
Nathan Kallus · 2020
Later among the works it cites.
‘‘Optimal doubly robust estimation of heterogeneous causal effects’’
Edward Kennedy · 2020
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‘‘Robust estimation of causal effects via a high-dimensional covariate balancing propensity score’’
Yang Ning, Peng Sida and Kosuke Imai · 2020
Later among the works it cites.
‘‘Reproducing Kernel Methods for Nonparametric and Semiparametric Treatment Effects’’
Rahul Singh, Liyuan Xu and Arthur Gretton · 2020
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‘‘Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data’’
Zhiqiang Tan · 2020
Later among the works it cites.
‘‘Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations’’
Yixin Wang and Jose Zubizarreta · 2020
Later among the works it cites.
‘‘Generalized optimal matching methods for causal inference’’
Nathan Kallus · 2020
Later among the works it cites.
‘‘Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data’’
Zhiqiang Tan · 2020
Later among the works it cites.
‘‘Kernel Balancing: A flexible non-parametric weighting procedure for estimating causal effects’’
Chad Hazlett · 2020
Later among the works it cites.
‘‘Generalized optimal matching methods for causal inference’’
Nathan Kallus · 2020
Later among the works it cites.
‘‘Optimal doubly robust estimation of heterogeneous causal effects’’
Edward Kennedy · 2020
Later among the works it cites.
‘‘Robust estimation of causal effects via a high-dimensional covariate balancing propensity score’’
Yang Ning, Peng Sida and Kosuke Imai · 2020
Later among the works it cites.
‘‘Reproducing Kernel Methods for Nonparametric and Semiparametric Treatment Effects’’
Rahul Singh, Liyuan Xu and Arthur Gretton · 2020
Later among the works it cites.
‘‘Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data’’
Zhiqiang Tan · 2020
Later among the works it cites.
‘‘Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations’’
Yixin Wang and Jose Zubizarreta · 2020
Later among the works it cites.
‘‘Generalized optimal matching methods for causal inference’’
Nathan Kallus · 2020
Later among the works it cites.
‘‘Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data’’
Zhiqiang Tan · 2020
Later among the works it cites.
‘‘Finite-Sample Optimal Estimation and Inference on Average Treatment Effects Under Unconfoundedness’’
Timothy Armstrong and Michal Kolesár · 2021
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‘‘Multilevel calibration weighting for survey data’’
Eli Ben-Michael, Avi Feller and Erin Hartman · 2021
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‘‘The augmented synthetic control method’’
Eli Ben-Michael, Avi Feller and Jesse Rothstein · 2021
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‘‘On the implied weights of linear regression in causal inference’’
A. Chattopadhyay and J.. Zubizarreta · 2021
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‘‘Multivariate extensions of isotonic regression and total variation denoising via entire monotonicity and Hardy--Krause variation’’
Billy Fang, Adityanand Guntuboyina and Bodhisattva Sen · 2021
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‘‘Finite-Sample Optimal Estimation and Inference on Average Treatment Effects Under Unconfoundedness’’
Timothy Armstrong and Michal Kolesár · 2021
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‘‘Multilevel calibration weighting for survey data’’
Eli Ben-Michael, Avi Feller and Erin Hartman · 2021
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‘‘The augmented synthetic control method’’
Eli Ben-Michael, Avi Feller and Jesse Rothstein · 2021
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‘‘On the implied weights of linear regression in causal inference’’
A. Chattopadhyay and J.. Zubizarreta · 2021
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‘‘Multivariate extensions of isotonic regression and total variation denoising via entire monotonicity and Hardy--Krause variation’’
Billy Fang, Adityanand Guntuboyina and Bodhisattva Sen · 2021
Closest in time.