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Shu Yang
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Cited by
Year
Propensity score matching and subclassification in observational studies with multi‐level treatments
S Yang, GW Imbens, Z Cui, DE Faries, Z Kadziola
Biometrics 72 (4), 1055-1065, 2016
1452016
Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores
S Yang, P Ding
Biometrika 105 (2), 487-493, 2018
672018
Causal inference methods for combining randomized trials and observational studies: a review
B Colnet, I Mayer, G Chen, A Dieng, R Li, G Varoquaux, JP Vert, J Josse, ...
arXiv preprint arXiv:2011.08047, 2020
662020
Doubly robust inference when combining probability and non-probability samples with high dimensional data
S Yang, JK Kim, R Song
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020
632020
Statistical data integration in survey sampling: A review
S Yang, JK Kim
Japanese Journal of Statistics and Data Science 3, 625-650, 2020
592020
Combining multiple observational data sources to estimate causal effects
S Yang, P Ding
Journal of the American Statistical Association 115 (531), 1540-1554, 2020
592020
A review of spatial causal inference methods for environmental and epidemiological applications
BJ Reich, S Yang, Y Guan, AB Giffin, MJ Miller, A Rappold
International Statistical Review 89 (3), 605-634, 2021
552021
Fractional imputation in survey sampling: A comparative review
S Yang, JK Kim
502016
Causal inference with confounders missing not at random
S Yang, L Wang, P Ding
Biometrika 106 (4), 875-888, 2019
442019
Propensity score weighting for causal inference with clustered data
S Yang
Journal of Causal Inference 6 (2), 20170027, 2018
342018
Sensitivity analysis for unmeasured confounding in coarse structural nested mean models
S Yang, J Lok
Statistica Sinica, doi:10.5705/ss.202016.0133, 2017
342017
Factors associated with parent concern for child weight and parenting behaviors
KL Peyer, G Welk, L Bailey-Davis, S Yang, JK Kim
Childhood Obesity 11 (3), 269-274, 2015
332015
A note on multiple imputation for method of moments estimation
S Yang, JK Kim
Biometrika 103 (1), 244-251, 2016
312016
Elastic integrative analysis of randomised trial and real-world data for treatment heterogeneity estimation
S Yang, C Gao, D Zeng, X Wang
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023
272023
Improving trial generalizability using observational studies
D Lee, S Yang, L Dong, X Wang, D Zeng, J Cai
Biometrics 79 (2), 1213-1225, 2023
272023
Semiparametric estimation of structural failure time models in continuous-time processes
S Yang, K Pieper, F Cools
Biometrika 107 (1), 123-136, 2020
242020
Improved inference for heterogeneous treatment effects using real-world data subject to hidden confounding
S Yang, D Zeng, X Wang
arXiv preprint arXiv:2007.12922, 2020
212020
Integrative analysis of randomized clinical trials with real world evidence studies
L Dong, S Yang, X Wang, D Zeng, J Cai
arXiv e-prints, arXiv: 2003.01242, 2020
212020
Integration of survey data and big observational data for finite population inference using mass imputation
S Yang, JK Kim
arXiv preprint arXiv:1807.02817, 2018
212018
Multiply robust matching estimators of average and quantile treatment effects
S Yang, Y Zhang
Scandinavian Journal of Statistics 50 (1), 235-265, 2023
192023
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