Shu Yang

A SPATIAL CAUSAL ANALYSIS OF WILDLAND FIRE-CONTRIBUTED PM2.5 USING NUMERICAL MODEL OUTPUT

ANNALS OF APPLIED STATISTICS, 16(4), 2714–2731.

A multiplicative structural nested mean model for zero-inflated outcomes

Yu, M., Lu, W., Yang, S., & Ghosh, P. (2022, August 19). BIOMETRIKA, Vol. 8.

Discussion on "Spatial plus : A novel approach to spatial confounding" by Dupont, Wood, and Augustin

Reich, B. J., Yang, S., & Guan, Y. (2022, March 30). BIOMETRICS, Vol. 3.

Double score matching in observational studies with multi-level treatments

Zhao, H., Zhang, X., & Yang, S. (2022, August 29). COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, Vol. 8.

Doubly robust estimators for generalizing treatment effects on survival outcomes from randomized controlled trials to a target population

JOURNAL OF CAUSAL INFERENCE, 10(1), 415–440.

Estimating intervention effects on infectious disease control: The effect of community mobility reduction on Coronavirus spread

SPATIAL STATISTICS, 52.

Generalized propensity score approach to causal inference with spatial interference

Giffin, A., Reich, B. J., Yang, S., & Rappold, A. G. (2022, September 19). BIOMETRICS, Vol. 9.

Identifiability of causal effects with multiple causes and a binary outcome

BIOMETRIKA, 109(1), 265–272.

Improving trial generalizability using observational studies

Lee, D., Yang, S., Dong, L., Wang, X., Zeng, D., & Cai, J. (2022, January 11). BIOMETRICS, Vol. 1.

Matrix completion under complex survey sampling

Mao, X., Wang, Z., & Yang, S. (2022, September 19). ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, Vol. 9.

Multiply robust estimation of causal effects under principal ignorability

Jiang, Z., Yang, S., & Ding, P. (2022, May 20). JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, Vol. 5.

Multiply robust matching estimators of average and quantile treatment effects

Yang, S., & Zhang, Y. (2022, April 7). SCANDINAVIAN JOURNAL OF STATISTICS, Vol. 4.

Nearest neighbour ratio imputation with incomplete multinomial outcome in survey sampling

Gao, C., Thompson, K. J., Kim, J. K., & Yang, S. (2022, May 10). JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, Vol. 5.

Nonparametric Mass Imputation for Data Integration

JOURNAL OF SURVEY STATISTICS AND METHODOLOGY, 10(1), 1–24.

Outcome-adjusted balance measure for generalized propensity score model selection

JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 221, 188–200.

ROBUST INFERENCE OF CONDITIONAL AVERAGE TREATMENT EFFECTS USING DIMENSION REDUCTION

STATISTICA SINICA, 32, 547–567.

Semiparametric estimation of structural nested mean models with irregularly spaced longitudinal observations

BIOMETRICS, 78(3), 937–949.

Sensitivity analyses in longitudinal clinical trials via distributional imputation

Liu, S., Yang, S., Zhang, Y., & Liu, G. (2022, November 6). STATISTICAL METHODS IN MEDICAL RESEARCH, Vol. 11.

Spectral adjustment for spatial confounding

Guan, Y., Page, G. L., Reich, B. J., Ventrucci, M., & Yang, S. (2022, December 21). BIOMETRIKA, Vol. 12.

Statistical data integration in survey sampling: a review (vol 3, pg 625, 2020)

Yang, S., & Kim, J. K. (2022, March 28). JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE, Vol. 3.

Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data

Wu, L., & Yang, S. (2022, November 30). JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, Vol. 11.

Treatment-specific marginal structural Cox model for the effect of treatment discontinuation

Johnson, D., Pieper, K., & Yang, S. (2022, March 31). PHARMACEUTICAL STATISTICS, Vol. 3.

Utilizing stratified generalized propensity score matching to approximate blocked randomized designs with multiple treatment levels

Corder, N., & Yang, S. (2022, June 20). JOURNAL OF BIOPHARMACEUTICAL STATISTICS, Vol. 6.

A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications

INTERNATIONAL STATISTICAL REVIEW, Vol. 5.

Practical recommendations on double score matching for estimating causal effects

Zhang, Y., Yang, S., Ye, W., Faries, D. E., Lipkovich, I., & Kadziola, Z. (2021, December 26). STATISTICS IN MEDICINE, Vol. 12.

Risks associated with discontinuation of oral anticoagulation in newly diagnosed patients with atrial fibrillation: Results from the GARFIELD-AF Registry

Cools, F., Johnson, D., Camm, A. J., Bassand, J.-P., Verheugt, F. W. A., Yang, S., … Kakkar, A. K. (2021, July 23). JOURNAL OF THROMBOSIS AND HAEMOSTASIS, Vol. 7.

SMIM: A unified framework of survival sensitivity analysis using multiple imputation and martingale

Yang, S., Zhang, Y., Liu, G. F., & Guan, Q. (2021, September 20). BIOMETRICS, Vol. 9.

Ascertaining properties of weighting in the estimation of optimal treatment regimes under monotone missingness

STATISTICS IN MEDICINE, 39(25), 3503–3520.

Double score matching estimators of average and quantile treatment effects

https://arxiv.org/abs/2001.06049

Doubly robust inference when combining probability and non-probability samples with high dimensional data

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 1.

Estimating Average Treatment Effects Utilizing Fractional Imputation when Confounders are Subject to Missingness

https://arxiv.org/pdf/1905.11497

Estimating Average Treatment Effects Utilizing Fractional Imputation when Confounders are Subject to Missingness

JOURNAL OF CAUSAL INFERENCE, 8(1), 249–271.

Integrative analysis of randomized clinicaltrials with real world evidence studies

https://arxiv.org/pdf/2003.01242

Robust estimation for moment condition models with data missing not at random

Journal of Statistical Planning and Inference, 207, 246–254.

Statistical data integration in survey sampling: a review

https://arxiv.org/abs/2001.03259

Statistical data integration in survey sampling: a review

[Review of ]. JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE, 3(2), 625–650.

Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework

Scandinavian Journal of Statistics, 47(3), 839–861.

Causal inference with confounders missing not at random

Biometrika, 106(4), 875–888.

Combining Multiple Observational Data Sources to Estimate Causal Effects

Journal of the American Statistical Association, 6, 1–33.

Discussion of "Penalized Spline of Propensity Methods for Treatment Comparison" by Zhou, Elliott, and Little

Yang, S., & Zeng, D. (2019, January 2). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 114, pp. 31–32.

Flexible Imputation of Missing Data, 2nd ed.

Journal of the American Statistical Association, 114(527), 1421–1421.

Matrix completion for survey data prediction with multivariate missingness

https://arxiv.org/pdf/1907.08360

Muti-cause causal inference with unmeasured confounding and binary outcome

https://arxiv.org/pdf/1907.13323

Nearest Neighbor Imputation for General Parameter Estimation in Survey Sampling

In Advances in Econometrics (pp. 209–234).

Nonparametric mass imputation for data integration

(Joint Statistical Meetings Report No. #301796).

Semiparametric estimation of structural failure time models in continuous-time processes

Biometrika, 10.

Approximate Bayesian inference under informative sampling

BIOMETRIKA, 105(1), 91–102.

Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores

BIOMETRIKA, 105(2), 487–493.

Discussion: Dissecting Multiple Imputation from a Multi-phase Inference Perspective: What Happens When God's, Imputer's and Analyst's Models are Uncongenial? by X. Xie and X. L. Meng

Statistica Sinica.

Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms

LIFETIME DATA ANALYSIS, 24(2), 201–223.

Integration of survey and big observational data for finite population inference using mass imputation

https://arxiv.org/abs/1807.02817

Modeling survival distribution as a function of time to treatment discontinuation: A dynamic treatment regime approach

BIOMETRICS, 74(3), 900–909.

Propensity Score Weighting for Causal Inference with Clustered Data

Journal of Causal Inference, 6(2).

SENSITIVITY ANALYSIS FOR UNMEASURED CONFOUNDING IN COARSE STRUCTURAL NESTED MEAN MODELS

STATISTICA SINICA, 28(4), 1703–1723.

Semiparametric efficient estimation of structural nested mean models with irregularly spaced observations

https://arxiv.org/abs/1810.00042

A note on multiple imputation under complex sampling

Biometrika, 104(1), 221–228.

A semiparametric inference to regression analysis with missing covariates in survey data

Statistica Sinica, 27(1), 261–285.

God, devil and guru in the land of multiple imputation discussion

Statistica Sinica, 27(4), 1568–1573.

A goodness-of-fit test for structural nested mean models

Biometrika, 103(3), 734–741.

A note on multiple imputation for method of moments estimation

Biometrika, 103(1), 244–251.

Fractional Imputation in Survey Sampling: A Comparative Review

Statistical Science, 31(3), 415–432.

Jamming and advanced modular-based blind rendezvous algorithms for cognitive radio networks

2016 IEEE 17th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WOWMOM).

Propensity Score Matching and Subclassification in Observational Studies with Multi-Level Treatments

BIOMETRICS, 72(4), 1055–1065.

Factors Associated with Parent Concern for Child Weight and Parenting Behaviors

Childhood Obesity, 11(3), 269–274.

Likelihood-based Inference with Missing Data Under Missing-at-Random

Scandinavian Journal of Statistics, 43(2), 436–454.

Semiparametric estimation of spectral density function for irregular spatial data

https://arxiv.org/abs/1508.06886

Fractional hot deck imputation for robust inference under item nonresponse in survey sampling

Survey Methodology, 40(2), 211–230. https://lib.dr.iastate.edu/stat_las_pubs/116/

Variance estimation and kriging prediction for a class of non-stationary spatial models

Statistica Sinica.

Improved estimation for June Area Survey incorporating several information

Proceedings 59th ISI World Statistics Congress, 199–204.

Imputation methods for quantile estimation under missing at random

Statistics and Its Interface, 6(3), 369–377.

Parametric fractional imputation for mixed models with nonignorable missing data

Statistics and Its Interface, 6(3), 339–347.

A spatial causal analysis of wildland fire- contributed PM2.5 using numerical model output

Larsen, A., Yang, S., Rappold, A., & Reich, B. https://arxiv.org/pdf/2003.06037

A unified framework for causal inference with multiple imputation using martingale

Guan, Q., & Yang, S. https://arxiv.org/pdf/1911.04663

Causal inference of hazard ratio based on propensity score matching

Tang, S., Yang, S., Wang, T., Cui, Z., Li, L., & Faries, D. https://arxiv.org/pdf/1911.12430