Fetching the paper…
Reading the bibliography…
Inverse propensity weighting (IPW) is a popular method for estimating treatment effects from observational data.
On the application of probability theory to agricultural experiments. essay on principles. section 9
Neyman, J. (1923, 11) · 1923
Earlier work this paper cites.
On the fundamental lemma of neyman and pearson
Dantzig, G. B. and A. Wald (1951) · 1951
Earlier work this paper cites.
On a class of problems related to the random division of an interval
Darling, D. A. (1953, 06) · 1953
Earlier work this paper cites.
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. (1974) · 1974
Earlier work this paper cites.
Economic analysis of trade unionism
Johnson, G. (1975) · 1975
Earlier work this paper cites.
Consistent nonparametric regression
Stone, C. J. (1977, 07) · 1977
Earlier work this paper cites.
Regression quantiles
Koenker, R. W. and G. Bassett (1978) · 1978
Earlier work this paper cites.
Unionism and wages: A longitudinal analysis
Mellow, W. (1981) · 1981
Earlier work this paper cites.
Multivariate regression models for panel data
Chamberlain, G. (1982) · 1982
Earlier work this paper cites.
Longitudinal analyses of the effects of trade unions
Freeman, R. B. (1984) · 1984
Earlier work this paper cites.
On asymptotically efficient estimation in semiparametric models
Schick, A. (1986, 09) · 1986
Earlier work this paper cites.
Sensitivity analysis for certain permutation inferences in matched observational studies
Rosenbaum, P. R. (1987) · 1987
Earlier work this paper cites.
Kernel and Nearest-Neighbor Estimation of a Conditional Quantile
Bhattacharya, P. K. and A. K. Gangopadhyay (1990) · 1990
Earlier work this paper cites.
Estimation and testing of the union wage effect using panel data
Jakubson, G. (1991) · 1991
Earlier work this paper cites.
Large sample estimation and hypothesis testing
Newey, W. K. and D. McFadden (1994) · 1994
Earlier work this paper cites.
Estimation of regression-coefficients when some regressors are not always observed
Robins, J. M., A. Rotnitzky, and L. P. Zhao (1994) · 1994
Earlier work this paper cites.
Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models
Robins, J. M., A. Rotnitzky, and D. O. Scharfstein (2000) · 2000
Earlier work this paper cites.
The Elements of Statistical Learning
Hastie, T., R. Tibshirani, and J. Friedman (2001) · 2001
Earlier work this paper cites.
Estimation of causal effects using propensity score weighting: An application to data on right heart catheterization
Hirano, K. and G. W. Imbens (2002) · 2002
Earlier work this paper cites.
Covariance adjustment in randomized experiments and observational studies
Rosenbaum, P. R. (2002, 08) · 2002
Earlier work this paper cites.
Pattern-mixture and selection models for analysing longitudinal data with monotone missing patterns
Birmingham, J., A. Rotnitzky, and G. M. Fitzmaurice (2003) · 2003
Cited alongside, same era.
Quantile Regression
Koenker, R. (2005) · 2005
Cited alongside, same era.
Heterogeneity and causality
Rosenbaum, P. R. (2005) · 2005
Cited alongside, same era.
Quantile regression forests
Meinshausen, N. (2006, December) · 2006
Cited alongside, same era.
A distributional approach for causal inference using propensity scores
Tan, Z. (2006) · 2006
Cited alongside, same era.
Introduction to empirical processes and semiparametric inference
Kosorok, M. (2008) · 2008
Cited alongside, same era.
Confounding-robust policy improvement
Kallus, N. and A. Zhou (2018) · 2018
Later among the works it cites.
Identification of treatment effects under conditional partial independence
Masten, M. A. and A. Poirier (2018) · 2018
Later among the works it cites.
Shape-constrained partial identification of a population mean under unknown probabilities of sample selection
Miratrix, L. W., S. Wager, and J. R. Zubizarreta (2018) · 2018
Later among the works it cites.
Bounds on the conditional and average treatment effect with unobserved confounding factors
Yadlowsky, S., H. Namkoong, S. Basu, J. Duchi, and L. Tian (2018) · 2018
Later among the works it cites.
Generalized random forests
Athey, S., J. Tibshirani, and S. Wager (2019, 04) · 2019
Later among the works it cites.
Conditional quantile processes based on series or many regressors
Belloni, A., V. Chernozhukov, D. Chetverikov, and I. Fernández-Val (2019) · 2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Training, wages, and sample selection: Estimating sharp bounds on treatment effects
Lee, D. (2009) · 2009
Cited alongside, same era.
Design of Observational Studies
Rosenbaum, P. R. (2010) · 2010
Cited alongside, same era.
Sharp identification regions in models with convex moment predictions
Beresteanu, A., I. Molchanov, and F. Molinari (2011) · 2011
Cited alongside, same era.
Efficiency bounds for missing data models with semiparametric restrictions
Graham, B. S. (2011) · 2011
Cited alongside, same era.
Interval estimation of population means under unknown but bounded probabilities of sample selection
Aronow, P. M. and D. K. K. Lee (2013) · 2013
Cited alongside, same era.
Calibrating sensitivity analyses to observed covariates in observational studies
Hsu, J. Y. and D. S. Small (2013) · 2013
Cited alongside, same era.
Later among the works it cites.
Interval estimation of individual-level causal effects under unobserved confounding
Kallus, N., X. Mao, and A. Zhou (2019) · 2019
Later among the works it cites.
An interval estimation approach to sample selection bias
Tudball, M., Q. Zhao, R. Hughes, K. Tilling, and J. Bowden (2019) · 2019
Later among the works it cites.
Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap
Zhao, Q., D. S. Small, and B. B. Bhattacharya (2019) · 2019
Later among the works it cites.
Making sense of sensitivity: Extending omitted variables bias
Cinelli, C. and C. Hazlett (2020) · 2020
Later among the works it cites.
Flexible sensitivity analysis for observational studies without observable implications
Franks, A. M., A. D. Amour, and A. Feller (2020) · 2020
Later among the works it cites.
Causal rule ensemble: Interpretable inference of heterogeneous treatment effects
Lee, K., F. J. Bargagli-Stoffi, and F. Dominici (2020) · 2020
Later among the works it cites.
Assessing sensitivity to unconfoundedness: Estimation and inference
Masten, M. A., A. Poirier, and L. Zhang (2020) · 2020
Later among the works it cites.
Combining observational and experimental datasets using shrinkage estimators
Rosenman, E., G. Basse, A. Owen, and M. Baiocchi (2020) · 2020
Later among the works it cites.
Better Lee bounds
Semenova, V. (2020) · 2020
Later among the works it cites.
A calibrated sensitivity analysis for matched observational studies with application to the effect of second‐hand smoke exposure on blood lead levels in children
Zhang, B. and D. S. Small (2020) · 2020
Later among the works it cites.
Policy learning with observational data
Athey, S. and S. Wager (2021) · 2021
Closest in time.
Designing experiments informed by observational studies
Rosenman, E. T. R. and A. B. Owen (2021) · 2021
Closest in time.
Interpretable sensitivity analysis for balancing weights
Soriano, D., E. Ben-Michael, P. J. Bickel, A. Feller, and S. D. Pimentel (2021) · 2021
Closest in time.