Fetching the paper…
Reading the bibliography…
We consider the problem of combining data from observational and experimental sources to make causal conclusions.
Shrinkage estimators in online experiments
Dimmery, D., Bakshy, E., and Sekhon, J. (2019) · 1904
Earlier work this paper cites.
Inadmissibility of the usual estimator for the mean of a multivariate normal distribution
Stein, C. (1956) · 1956
Earlier work this paper cites.
Factors relevant to the validity of experiments in social settings
Campbell, D. T. (1957) · 1957
Earlier work this paper cites.
Multiple regression and estimation of the mean of a multivariate normal distribution
Baranchik, A. J. (1964) · 1964
Earlier work this paper cites.
Estimation of the mean of a multivariate normal distribution
Stein, C. M. (1981) · 1981
Earlier work this paper cites.
From stein’s unbiased risk estimates to the method of generalized cross validation
Li, K.-C. et al. (1985) · 1985
Earlier work this paper cites.
Asymptotic optimality of c _ l c\_l and generalized cross-validation in ridge regression with application to spline smoothing
Li, K.-C. et al. (1986) · 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.
Statistical power analysis for the behavioral sciences
Cohen, J. (1988) · 1988
Earlier work this paper cites.
A james-stein type estimator for combining unbiased and possibly biased estimators
Green, E. J. and Strawderman, W. E. (1991) · 1991
Cited alongside, same era.
Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women’s Health Initiative randomized controlled trial
Writing Group for the Women’s Health Initiative Investigators (2002) · 2002
Cited alongside, same era.
On minimax estimation of a normal mean vector for general quadratic loss
Strawderman, W. E. et al. (2003) · 2003
Cited alongside, same era.
Improved estimation for multiple means with heterogeneous variances
Green, E. J., Strawderman, W. E., Amateis, R. L., and Reams, G. A. (2005) · 2005
Cited alongside, same era.
Generalizing evidence from randomized clinical trials to target populations: the actg 320 trial
Cole, S. R. and Stuart, E. A. (2010) · 2010
Cited alongside, same era.
From sate to patt: combining experimental with observational studies to estimate population treatment effects
Hartman, E., Grieve, R., Ramsahai, R., and Sekhon, J. S. (2015) · 2015
Later among the works it cites.
Causal inference and the data-fusion problem
Bareinboim, E. and Pearl, J. (2016) · 2016
Later among the works it cites.
Combining observational and experimental data to find heterogeneous treatment effects
Peysakhovich, A. and Lada, A. (2016) · 2016
Later among the works it cites.
General forms of finite population central limit theorems with applications to causal inference
Li, X. and Ding, P. (2017) · 2017
Later among the works it cites.
Removing hidden confounding by experimental grounding
Kallus, N., Puli, A. M., and Shalit, U. (2018) · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Bayesian nonparametric modeling for causal inference
Hill, J. L. (2011) · 2011
Cited alongside, same era.
The use of propensity scores to assess the generalizability of results from randomized trials
Stuart, E. A., Cole, S. R., Bradshaw, C. P., and Leaf, P. J. (2011) · 2011
Cited alongside, same era.
Large-scale inference: empirical Bayes methods for estimation, testing, and prediction
Efron, B. (2012) · 2012
Cited alongside, same era.
Sure estimates for a heteroscedastic hierarchical model
Xie, X., Kou, S., and Brown, L. D. (2012) · 2012
Cited alongside, same era.
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Imbens, G. W. and Rubin, D. B. (2015a)
Cited in the paper.
Causal inference in statistics, social, and biomedical sciences
Imbens, G. W. and Rubin, D. B. (2015b)
Cited in the paper.
Rosenman, E., Owen, A. B., Baiocchi, M., and Banack, H. (2018) · 2018
Later among the works it cites.
Estimation and inference of heterogeneous treatment effects using random forests
Wager, S. and Athey, S. (2018) · 2018
Later among the works it cites.
The surrogate index: Combining short-term proxies to estimate long-term treatment effects more rapidly and precisely
Athey, S., Chetty, R., Imbens, G. W., and Kang, H. (2019) · 2019
Later among the works it cites.
Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap
Zhao, Q., Small, D. S., and Bhattacharya, B. B. (2019) · 2019
Later among the works it cites.