Ying Yan, School of Mathematics, Sun Yat-sen University

Academic Position:

• 2018-  : Associate Professor, Sun Yat-sen University (中山大学), China

• 2015-2017: Assistant Professor, University of Calgary, Canada

• 2014-2015: Postdoctoral Researcher, University of North Carolina at Chapel Hill, United States

Education:

• 2010-2014: Ph.D. in Statistics, University of Waterloo, Canada 

• 2008-2010: M.Math. in Statistics, University of Waterloo, Canada

• 2004-2008: B.S. in Mathematics, University of Science and Technology of China (中国科学技术大学), China

Research Interest:

• Biostatistics, Causal inference, Econometrics, Machine learning, Measurement error, Missing data, Treatment effect

Peer-Reviewed Publication/Submitted Manuscript († Supervised Student):

• X. Wen†  and Y. Yan (2025). Covariate balancing with measurement error, arXiv:2406.09163.  Statistics in Medicine, Revision.

• X. Wen†, L. Qin†, H. Wu†, and Y. Yan (2025). Survival analysis under the Aalen's additive hazards model with covariate measurement error: Application to causal mediation analysis.  Statistics in Medicine, Revision.

• X. Li† , Q. Zhou† , S. Ding , W. Pan,  R. Liu, Y. Yan, and C. Huang (2025).  Shape-based partially linear single-index Cox model for Alzheimer’s disease convention.  Statistics in Medicine, Revision.

• Y. Yan and L. Shen†  (2025). Mediation analysis with exposure-mediator interaction and covariate measurement error under the additive hazards model, Biometrical Journal, 67(1), e70035.

• X. Li†, Q. Zhou†, Y. Wu, and Y. Yan (2025). Multicategory matched learning for estimating optimal individualized treatment rules in observational studies with application to a hepatocellular carcinoma study, Statistical Methods in Medical Research, 34(3), 508-522.

• Y. Yan (2025). Balancing covariate distributions with maximum mean discrepancy for causal inference: A duality viewpoint.

• X. Wen† and Y. Yan (2025). Inference of treatment effects using restricted mean survival times in the presence of covariate measurement error: A corrected entropy balancing approach.

• X. Li†  and Y. Yan (2024). Matching-based policy learning, arXiv:2407.08468. 

• Y. Dai† and Y. Yan (2024). Mahalanobis balancing: A multivariate perspective on approximate covariate balancing, Scandinavian Journal of Statistics, 51(4), 1450-1471. 

• Y. Tan†, X. Wen†, W. Liang†, and Y. Yan (2024). Empirical likelihood-based weighted estimation of average treatment effects in randomized clinical trials with missing outcomes, Statistics and Its Interface, 17(4), 699-714. 

• Y. Yan, M. Ren†, and A. de Leon (2024). Measurement error correction in mediation analysis under the additive hazards model, Communications in Statistics-Simulation and Computation, 53(10), 5083-5099.

• Y. Yan and M. Ren† (2023). Consistent inverse probability of treatment weighted estimation of the average treatment effect with mismeasured time-dependent confounders, Statistics in Medicine, 42(4), 517-535.

• W. Liang† and Y. Yan (2022). Empirical likelihood-based estimation and inference in randomized controlled trials with high-dimensional covariates, Statistics and Its Interface, 15(3), 283-301.

• G. Y. Yi and Y. Yan (2021). Estimation and hypothesis testing with error-contaminated survival data under possibly misspecified measurement error models, Canadian Journal of Statistics, 49(3), 853-874.

• G. Y. Yi, Y. Yan, X. Liao, and D. Spiegelman (2019). Parametric regression analysis with covariate misclassification in main study/validation study designs, International Journal of Biostatistics, 15(1), 20170002. 

• N.Gugala, J. Lemire, K. Chatfield-Reed, Y. Yan, G. Chua, and R. J. Turner (2018). Using a chemical genetic screen to enhance our understanding of the antibacterial properties of silver, Genes, 9(7), 344.

• Y. Yan, H. Zhou, and J. Cai (2017). Improving efficiency of parameter estimation in case-cohort studies with multivariate failure time data, Biometrics, 73(3), 1042-1052.

• Y. Yan and G. Y. Yi (2016). A class of functional methods for error-contaminated survival data under additive hazards models with replicate measurements, Journal of the American Statistical Association, 111(514), 684-695. 

• Y. Yan and G. Y. Yi (2016). Analysis of error-prone survival data under additive hazards models: measurement error effects and adjustments, Lifetime Data Analysis, 22(3), 321-342. 

• Y. Yan and G. Y. Yi (2015). A corrected profile likelihood method for survival data with covariate measurement error under the Cox model,  Canadian Journal of Statistics, 43(3), 454-480. 

• C. Wu and Y. Yan (2012). Empirical likelihood inference for two-sample problems, Statistics and Its Interface, 5(3), 345-354.

Working Project:

• On entropy balancing for causal generalization using summary information.

• Optimal statistical inference for case-cohort studies with multivariate survival data.

• Covariate balancing and treatment effect inference in multi-arm studies in the presence of limited overlaps.

• Matching-based policy learning with a continuous or multicategory treatment.

• Data integration when some covariates are missing.

• Propensity score matching with measurement error. 

• Other topics: manifold-valued data, mediation analysis with imaging data, mismeasured continuous treatment,  functional treatment effect.

Research Grant & Award:

• 2018- : 主持国家自然科学基金青年项目、广东省自然科学基金面上项目、中央高校基本科研业务费、珠海市政府项目、中山大学人才基本启动费等；参与国家自然科学基金重大项目、国家自然科学基金面上项目、广州市科技计划项目等

• 2017, The GREAT Supervisor Award, University of Calgary.

• 2016-2020, Principal Investigator (PI), Discovery Grant, Natural Sciences and Engineering Research Council of Canada (NSERC).

• 2016-2017, Co-PI, Canadian Kidney Cancer Information System (CKCis); Breast Cancer Society of Canada (BCSC).

• 2015-2017, PI, Start-up Grant, University of Calgary.

• 2015, Pierre Robillard Award, Statistical Society of Canada.

• 2013, Sprott Scholarship, University of Waterloo.

Service:

• 中国现场统计研究会因果推断分会理事，广东省现场统计学会理事

Reviewer:

• Biometrics, Biostatistics, Canadian Journal of Statistics, Computational Statistics & Data Analysis, Electronic Journal of Statistics, Journal of the American Statistical Association, Journal of the Royal Statistical Society: Series C, Lifetime Data Analysis, Statistics in Medicine, Statistical Methods in Medical Research, Statistica Sinica, Technometrics, etc.