Shu Yang
Citata da
Citata da
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
Fractional imputation in survey sampling: A comparative review
S Yang, JK Kim
Statistical Science 31 (3), 415-432, 2016
Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores
S Yang, P Ding
Biometrika 105 (2), 487-493, 2018
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
A note on multiple imputation for method of moments estimation
S Yang, JK Kim
Biometrika 103 (1), 244-251, 2016
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
Combining multiple observational data sources to estimate causal effects
S Yang, P Ding
Journal of the American Statistical Association, 2019
A note on multiple imputation under complex sampling
JK Kim, S Yang
Biometrika 104 (1), 221-228, 2017
Propensity score weighting for causal inference with clustered data
S Yang
Journal of Causal Inference 6 (2), 2018
Fractional hot deck imputation for robust inference under item nonresponse in survey sampling
JK Kim, S Yang
Survey Methodology 40 (2), 211, 2014
Parametric fractional imputation for mixed models with nonignorable missing data
S Yang, JK Kim, Z Zhu
Statistics and Its Interface 6 (3), 339-347, 2013
Causal inference with confounders missing not at random
S Yang, L Wang, P Ding
Biometrika 106 (4), 875-888, 2019
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
Predictive mean matching imputation in survey sampling
S Yang, JK Kim
arXiv preprint arXiv:1703.10256, 2017
Sensitivity analysis for unmeasured confounding in coarse structural nested mean models
S Yang, J Lok
Statistica Sinica, doi:10.5705/ss.202016.0133, 2017
Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms
JJ Lok, S Yang, B Sharkey, MD Hughes
Lifetime data analysis 24 (2), 201-223, 2018
Approximate Bayesian inference under informative sampling
Z Wang, JK Kim, S Yang
Biometrika 105 (1), 91-102, 2018
A goodness-of-fit test for structural nested mean models
S Yang, JJ Lok
Biometrika 103 (3), 734-741, 2016
Imputation methods for quantile estimation under missing at random
S Yang, JK Kim, DW Shin
Statistics and its Interface 6 (3), 369-377, 2013
Statistical data integration in survey sampling: A review
S Yang, JK Kim
Japanese Journal of Statistics and Data Science, 1-26, 2020
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