Research Assistant Professor, Survey Research Center, Institute for Social Research
Yajuan Si was an assistant professor jointly in the Department of Biostatistics & Medical Informatics and the Department of Population Health Sciences at the University of Wisconsin (UW), Madison. She is affiliated in the UW Survey Center and Department of Statistics. Before joining UW in 2014, Yajuan was a Postdoctoral Research Scholar at Columbia University, NYC. In September 2012, she obtained her Ph.D degree on Statistical Science from Duke University. Dr Si’s research lies in cutting-edge methodology development in streams of Bayesian statistics, complex survey inference, missing data imputation, causal inference, and data confidentiality protection. Currently she is leading a NSF funded project to build a unified framework in sample weighted inferences and a NIH funded grant to profile missing data in electronic health records. Yajuan has extensive collaboration experiences with health services researchers and epidemiologists to improve healthcare and public health practice, and she has been providing statistical support to solve sampling and analysis issues on health and social science surveys.
- Makela,S.; Si,Yajuan and Gelman,A. (2017). Graphical Visualization of Polling Results. In Atkeson,Lonna R. and Alvarez,R. M. (Ed.), The Oxford Handbook of Polling and Polling Methods. Oxford University Press:Oxford, United Kingdom.
- Early,D. M.; Berg,J. K.; Alicea,S.; Si,Yajuan; Aber,J. L.; Ryan,R. M. and Deci,E. L. (2016). The Impact of Every Classroom, Every Day on High School Student Achievement: Results from a School-Randomized Trial. Journal of Research on Educational Effectiveness, 9, 3-29.
- Neuman,Heather B.; Schumacher,Jessica R.; Francescatti,Amanda B.; Adesoye,Taiwo; SB,Edge; ES,Burnside; DJ,Vanness; M,Yu; Si,Yajuan; D,McKellar; DP,Winchester and Greenberg,Caprice C. (2016). Utility of Clinical Breast Exams in Detecting Local-Regional Breast Events After Breast-Conservation in Women with a Personal History of High-Risk Breast Cancer. Annals of Surgical Oncology, 23(10), 3385-3391.
- Si,Yajuan; Reiter,Jerome P. and Hillygus,D. S. (2016). Bayesian Latent Pattern Mixture Models for Handling Attrition in Panel Studies with Refreshment Samples. Annals of Applied Statistics, 10(1), 118-143.
- Si,Yajuan; Pillai,Natesh S. and Gelman,Andrew (2015). Bayesian Nonparametric Weighted Sampling Inference. Bayesian Anal., 10(3), 605-625.
- Si,Yajuan; Reiter,Jerome P. and Hillygus,D. S. (2015). Semi-Parametric Selection Models for Potentially Non-Ignorable Attrition in Panel Studies with Refreshment Samples. Political Analysis, 23(1), 92-112.
- Makela,Susanna; Si,Yajuan and Gelman,Andrew (2014). Statistical Graphics for Survey Weights. Revista Colombiana De Estadística, 37(2), 285-295.
- Deng,Yiting; Hillygus,D. S.; Reiter,Jerome P.; Si,Yajuan and Zheng,Siyu (2013). Handling Attrition in Longitudinal Studies: The Case for Refreshment Samples. Statistical Science, 28(2), 238-256.
- Si,Yajuan and Reiter,Jerome P. (2013). Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys. Journal of Educational and Behavioral Statistics, 38(5), 499-521.
- Si,Yajuan and Reiter,JP (2011). A Comparison of Posterior Simulation and Inference by Combining Rules for Multiple Imputation. Journal of Statistical Theory and Practice, 5, 335-347.