Fetching the paper…
Reading the bibliography…
For observational studies, we study the sensitivity of causal inference when treatment assignments may depend on unobserved confounders.
Smoking and lung cancer: Recent evidence and a discussion of some questions
J. Cornfield, W. Haenszel, E. C. Hammond, A. M. Lilienfeld, M. B. Shimkin, and E. L. Wynder · 1959
Earlier work this paper cites.
Optimal asymptotic tests of composite statistical hypotheses
J. Neyman · 1959
Earlier work this paper cites.
Theory of Approximation of Functions of a Real Variable , volume 34
A. F. Timan · 1963
Earlier work this paper cites.
Inequalities for the norms of a function and its derivatives in metric L p
V. Gabushin · 1967
Earlier work this paper cites.
Optimization by Vector Space Methods
D. Luenberger · 1969
Earlier work this paper cites.
Optimal rates of convergence for nonparametric estimators
C. J. Stone · 1980
Earlier work this paper cites.
Nonparametric maximum likelihood estimation by the method of sieves
S. Geman and C. R. Hwang · 1982
Earlier work this paper cites.
Ten Lectures on Wavelets , volume 61
I. Daubechies · 1992
Earlier work this paper cites.
Convergence rates and asymptotic normality for series estimators
W. K. Newey · 1997
Earlier work this paper cites.
Sieve extremum estimates for weakly dependent data
X. Chen and X. Shen · 1998
Earlier work this paper cites.
On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
J. Hahn · 1998
Earlier work this paper cites.
Projection estimation in multiple regression with application to functional ANOVA models
J. Z. Huang et al · 1998
Earlier work this paper cites.
Variational Analysis
R. T. Rockafellar and R. J. B. Wets · 1998
Earlier work this paper cites.
Improved rates and asymptotic normality for nonparametric neural network estimators
X. Chen and H. White · 1999
Earlier work this paper cites.
Adjusting for nonignorable drop-out using semiparametric nonresponse models
D. O. Scharfstein, A. Rotnitzky, and J. M. Robins · 1999
Earlier work this paper cites.
Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models
J. M. Robins, A. Rotnitzky, and D. O. Scharfstein · 2000
Earlier work this paper cites.
Empirical Processes in M-Estimation
S. van de Geer · 2000
Earlier work this paper cites.
A Distribution-Free Theory of Nonparametric Regression
L. Györfi, M. Kohler, A. Krzyżak, and H. Walk · 2002
Earlier work this paper cites.
Efficient estimation of average treatment effects using the estimated propensity score
K. Hirano, G. Imbens, and G. Ridder · 2003
Earlier work this paper cites.
Sensitivity to exogeneity assumptions in program evaluation
G. W. Imbens · 2003
Earlier work this paper cites.
Convex Optimization
S. Boyd and L. Vandenberghe · 2004
Cited alongside, same era.
Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures
B. A. Brumback, M. A. Hernán, S. J. P. A. Haneuse, and J. M. Robins · 2004
Cited alongside, same era.
Nonparametric estimation of average treatment effects under exogeneity: A review
G. W. Imbens · 2004
Cited alongside, same era.
Doubly robust estimation in missing data and causal inference models
H. Bang and J. M. Robins · 2005
Cited alongside, same era.
Large sample properties of matching estimators for average treatment effects
A. Abadie and G. W. Imbens · 2006
Cited alongside, same era.
Large sample sieve estimation of semi-nonparametric models
X. Chen · 2007
Cited alongside, same era.
Causal Inference for Statistics, Social, and Biomedical Sciences
G. Imbens and D. Rubin · 2015
Later among the works it cites.
Adaptive concentration of regression trees, with application to random forests
S. Wager and G. Walther · 2015
Later among the works it cites.
Recursive partitioning for heterogeneous causal effects
S. Athey and G. Imbens · 2016
Later among the works it cites.
XGBoost: A scalable tree boosting system
T. Chen and C. Guestrin · 2016
Later among the works it cites.
Lecture notes on probability theory: Stanford statistics 310
A. Dembo · 2016
Later among the works it cites.
Sensitivity analysis for multiple comparisons in matched observational studies through quadratically constrained linear programming
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Spline Functions: Basic Theory
L. Schumaker · 2007
Cited alongside, same era.
Comment: Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data
A. A. Tsiatis and M. Davidian · 2007
Cited alongside, same era.
A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies
J. L. Bosco, R. A. Silliman, S. S. Thwin, A. M. Geiger, D. S. Buist, M. N. Prout, M. U. Yood, R. Haque, F. Wei, and T. L. Lash · 2010
Cited alongside, same era.
Design of Observational Studies
P. R. Rosenbaum · 2010
Cited alongside, same era.
Bayesian nonparametric modeling for causal inference
J. L. Hill · 2011
Cited alongside, same era.
Weight trimming and propensity score weighting
B. K. Lee, J. Lessler, and E. A. Stuart · 2011
Cited alongside, same era.
C. B. Fogarty and D. S. Small · 2016
Later among the works it cites.
Meta-learners for estimating heterogeneous treatment effects using machine learning
S. R. Künzel, J. S. Sekhon, P. J. Bickel, and B. Yu · 2017
Later among the works it cites.
Shape-constrained partial identification of a population mean under unknown probabilities of sample selection
L. W. Miratrix, S. Wager, and J. R. Zubizarreta · 2017
Later among the works it cites.
Sensitivity analysis in observational research: introducing the e-value
T. J. VanderWeele and P. Ding · 2017
Later among the works it cites.
Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap
Q. Zhao, D. Small, and B. Bhattacharya · 2017
Later among the works it cites.
Double/debiased machine learning for treatment and structural parameters
V. Chernozhukov, D. Chetverikov, M. Demirer, E. Duflo, C. Hansen, W. Newey, and J. Robins · 2018
Closest in time.
Confounding-robust policy improvement
N. Kallus and A. Zhou · 2018
Closest in time.
Odds Ratios–Current Best Practice and Use
E. C. Norton, B. E. Dowd, and M. L. Maciejewski · 2018
Closest in time.
Estimation and inference of heterogeneous treatment effects using random forests
S. Wager and S. Athey · 2018
Closest in time.
Generalized random forests
S. Athey, J. Tibshirani, and S. Wager · 2019
Closest in time.
Flexible sensitivity analysis for observational studies without observable implications
A. M. Franks, A. D’Amour, and A. Feller · 2019
Closest in time.
Interval estimation of individual-level causal effects under unobserved confounding
N. Kallus, X. Mao, and A. Zhou · 2019
Closest in time.
Quasi-oracle estimation of heterogeneous treatment effects
X. Nie and S. Wager · 2019
Closest in time.
Optimal doubly robust estimation of heterogeneous causal effects
E. H. Kennedy · 2020
Closest in time.