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In observational studies, identification of ATEs is generally achieved by assuming that the correct set of confounders has been measured and properly included in the relevant models.
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Donald B Rubin · 1974
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The effectiveness of right heart catheterization in the initial care of critically ill patients
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Aad W. van der Vaart and John A. Wellner · 1996
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Dual and simultaneous sensitivity analysis for matched pairs
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Danyu Y Lin, Bruce M Psaty, and Richard A Kronmal · 1998
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Asymptotic statistics , volume 3
Aad W Van der Vaart · 2000
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Methods for conducting sensitivity analysis of trials with potentially nonignorable competing causes of censoring
Andrea Rotnitzky, Daniel Scharfstein, Ting-Li Su, and James Robins · 2001
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On the coherence of expected shortfall
Carlo Acerbi and Dirk Tasche · 2002
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[covariance adjustment in randomized experiments and observational studies]: Comment
James M Robins · 2002
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Covariance adjustment in randomized experiments and observational studies
Paul R Rosenbaum et al · 2002
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Semiparametric statistics
Aad W. van der Vaart · 2002
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Sensitivity to exogeneity assumptions in program evaluation
Guido W Imbens · 2003
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Unified methods for censored longitudinal data and causality
Mark J Van der Laan, MJ Laan, and James M Robins · 2003
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Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures
Babette A Brumback, Miguel A Hernán, Sebastien JPA Haneuse, and James M Robins · 2004
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Confidence intervals for partially identified parameters
Guido W Imbens and Charles F Manski · 2004
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Design sensitivity in observational studies
Paul R Rosenbaum · 2004
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A distribution-free theory of nonparametric regression
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Instruments for causal inference: an epidemiologist’s dream?
Miguel A Hernán and James M Robins · 2006
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Differential effects and generic biases in observational studies
Paul R Rosenbaum · 2006
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Ignorance and uncertainty regions as inferential tools in a sensitivity analysis
Stijn Vansteelandt, Els Goetghebeur, Michael G Kenward, and Geert Molenberghs · 2006
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Fast learning rates for plug-in classifiers
Jean-Yves Audibert, Alexandre B Tsybakov, et al · 2007
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Anastasios Tsiatis · 2007
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Nonparametric bounds and sensitivity analysis of treatment effects
Amy Richardson, Michael G Hudgens, Peter B Gilbert, and Jason P Fine · 2014
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Targeted learning of an optimal dynamic treatment, and statistical inference for its mean outcome
Mark J van der Laan and Alexander R Luedtke · 2014
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Robust inference on average treatment effects with possibly more covariates than observations
Max H Farrell · 2015
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The statistics of sensitivity analyses
Alexander R Luedtke, Ivan Diaz, and Mark J van der Laan · 2015
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Minimax-optimal nonparametric regression in high dimensions
Yun Yang and Surya T Tokdar · 2015
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The highly adaptive lasso estimator
David Benkeser and Mark Van Der Laan · 2016
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Using selection on observed variables to assess bias from unobservables when evaluating swan-ganz catheterization
Joseph G Altonji, Todd E Elder, and Christopher R Taber · 2008
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Introduction to empirical processes and semiparametric inference
Michael R Kosorok · 2008
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Higher order influence functions and minimax estimation of nonlinear functionals
James Robins, Lingling Li, Eric Tchetgen, Aad van der Vaart, et al · 2008
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Improving point and interval estimators of monotone functions by rearrangement
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Semiparametric and nonparametric methods in econometrics , volume 12
Joel L Horowitz · 2009
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Double machine learning for treatment and causal parameters
Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, and Whitney K Newey · 2016
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Sensitivity analysis without assumptions
Peng Ding and Tyler J VanderWeele · 2016
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Additive approximations in high dimensional nonparametric regression via the salsa
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Statistical inference for the mean outcome under a possibly non-unique optimal treatment strategy
Alexander R Luedtke and Mark J Van Der Laan · 2016
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A generally efficient targeted minimum loss based estimator based on the highly adaptive lasso
Mark van der Laan · 2017
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Sensitivity analysis in observational research: introducing the e-value
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Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap
Qingyuan Zhao, Dylan S Small, and Bhaswar B Bhattacharya · 2017
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Nonparametric causal effects based on incremental propensity score interventions
Edward H Kennedy · 2018
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Sharp instruments for classifying compliers and generalizing causal effects
Edward H Kennedy, Sivaraman Balakrishnan, and Max G’Sell · 2018
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Bounds on the conditional and average treatment effect in the presence of unobserved confounders
Steve Yadlowsky, Hongseok Namkoong, Sanjay Basu, John Duchi, and Lu Tian · 2018
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Survivor-complier effects in the presence of selection on treatment, with application to a study of prompt icu admission
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Influence of parental smoking on the use of alcohol and illicit drugs among adolescents
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Alcohol use and misuse among school-going adolescents in thailand: results of a national survey in 2015
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