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The ability to generalize experimental results from randomized control trials (RCTs) across locations is crucial for informing policy decisions in targeted regions.
Smoking and lung cancer: recent evidence and a discussion of some questions
Jerome Cornfield, William Haenszel, E Cuyler Hammond, Abraham M Lilienfeld, Michael B Shimkin, and Ernst L Wynder · 1959
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The central role of the propensity score in observational studies for causal effects
Paul R Rosenbaum and Donald B Rubin · 1983
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Sensitivity analysis for certain permutation inferences in matched observational studies
Paul R Rosenbaum · 1987
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Inferences for case-control and semiparametric two-sample density ratio models
Jing Qin · 1998
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Experimental and quasi-experimental designs for generalized causal inference
Thomas D Cook, Donald Thomas Campbell, and William Shadish · 2002
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Sensitivity to exogeneity assumptions in program evaluation
Guido W Imbens · 2003
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Predicting the efficacy of future training programs using past experiences at other locations
V Joseph Hotz, Guido W Imbens, and Julie H Mortimer · 2005
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Evaluating the differential effects of alternative welfare-to-work training components: A reanalysis of the california gain program
V Joseph Hotz, Guido W Imbens, and Jacob A Klerman · 2006
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A distributional approach for causal inference using propensity scores
Zhiqiang Tan · 2006
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Covariate shift by kernel mean matching
Arthur Gretton, Alex Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, and Bernhard Schölkopf · 2009
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Generalizing evidence from randomized clinical trials to target populations: The actg 320 trial
Stephen R Cole and Elizabeth A Stuart · 2010
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Design of observational studies , volume 10
Paul R Rosenbaum · 2010
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Subsidizing vocational training for disadvantaged youth in colombia: evidence from a randomized trial
Orazio Attanasio, Adriana Kugler, and Costas Meghir · 2011
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Estimating treatment effect via simple cross design synthesis
Eloise E Kaizar · 2011
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A new u-statistic with superior design sensitivity in matched observational studies
Paul R Rosenbaum · 2011
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Sensitivity analysis for causal inference using inverse probability weighting
Changyu Shen, Xiaochun Li, Lingling Li, and Martin C Were · 2011
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The use of propensity scores to assess the generalizability of results from randomized trials
Elizabeth A Stuart, Stephen R Cole, Catherine P Bradshaw, and Philip J Leaf · 2011
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Interval estimation of population means under unknown but bounded probabilities of sample selection
Peter M Aronow and Donald KK Lee · 2012
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Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies
Jens Hainmueller · 2012
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Density ratio estimation in machine learning
Masashi Sugiyama, Taiji Suzuki, and Takafumi Kanamori · 2012
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Meta-transportability of causal effects: A formal approach
Elias Bareinboim and Judea Pearl · 2013
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External validity in policy evaluations that choose sites purposively
Robert B Olsen, Larry L Orr, Stephen H Bell, and Elizabeth A Stuart · 2013
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The use of propensity scores and observational data to estimate randomized controlled trial generalizability bias
Taylor R Pressler and Eloise E Kaizar · 2013
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Transportability from multiple environments with limited experiments: Completeness results
Elias Bareinboim and Judea Pearl · 2014
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Covariate balancing propensity score
Kosuke Imai and Marc Ratkovic · 2014
High dimensional propensity score estimation via covariate balancing, 2017
Yang Ning, Sida Peng, and Kosuke Imai · 2017
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Zhiqiang Tan · 2017
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Sensitivity analysis in observational research: introducing the e-value
Tyler J VanderWeele and Peng Ding · 2017
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Minimal approximately balancing weights: asymptotic properties and practical considerations
Yixin Wang and José R Zubizarreta · 2017
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Transportability of trial results using inverse odds of sampling weights
Daniel Westreich, Jessie K Edwards, Catherine R Lesko, Elizabeth Stuart, and Stephen R Cole · 2017
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External validity: From do-calculus to transportability across populations
Judea Pearl and Elias Bareinboim · 2014
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Weighted m-statistics with superior design sensitivity in matched observational studies with multiple controls
Paul R Rosenbaum · 2014
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Generalizing the results from social experiments: Theory and evidence from mexico and india
Michael Gechter · 2015
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Stable weights that balance covariates for estimation with incomplete outcome data
José R Zubizarreta · 2015
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Susan Athey, Raj Chetty, Guido Imbens, and Hyunseung Kang · 2016
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Causal inference and the data-fusion problem
Elias Bareinboim and Judea Pearl · 2016
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Approximate residual balancing: debiased inference of average treatment effects in high dimensions
Susan Athey, Guido W Imbens, and Stefan Wager · 2018
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Magdalena Bennett, Juan Pablo Vielma, and Jose R Zubizarreta · 2018
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Balanced policy evaluation and learning
Nathan Kallus · 2018
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Removing hidden confounding by experimental grounding
Nathan Kallus, Aahlad Manas Puli, and Uri Shalit · 2018
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Propensity score methods for merging observational and experimental datasets
Evan Rosenman, Art B Owen, Michael Baiocchi, and Hailey Banack · 2018
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Zhiqiang Tan · 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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Sparsity double robust inference of average treatment effects
Jelena Bradic, Stefan Wager, and Yinchu Zhu · 2019
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From local to global: External validity in a fertility natural experiment
Rajeev Dehejia, Cristian Pop-Eleches, and Cyrus Samii · 2019
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Minimax linear estimation of the retargeted mean
David A Hirshberg, Arian Maleki, and Jose Zubizarreta · 2019
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Covariate balancing propensity score by tailored loss functions
Qingyuan Zhao · 2019
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Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap
Qingyuan Zhao, Dylan S Small, and Bhaswar B Bhattacharya · 2019
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Predicting with proxies: Transfer learning in high dimension
Hamsa Bastani · 2020
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Augmented minimax linear estimation
David A Hirshberg and Stefan Wager · 2021
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