Lu Wang is Associate Professor of Biostatistics. She received her Ph.D in Biostatistics from Harvard University in 2008 and joined the faculty at the University of Michigan in the same year. Dr. Wang's research focuses on statistical methods for evaluating dynamic treatment regimes, personalized health care, nonparametric and semiparametric regressions, missing data analysis, functional data analysis, and longitudinal (correlated/clustered) data analysis. She has been collaborating with investigators at M.D. Anderson Cancer Center, University of Michigan Medical School, and Harvard School of Public Health.
- BIOSTAT601: Probability and Distribution Theory (2008F, 2010F, 2011F, 2012F, 2013F, 2014F)
- BIOSTAT653: Analysis of Correlated/Longitudinal Data (2010W, 2011W, 2015W)
- BIOSTAT830: Statistical Methods for Causal Inference and Dynamic Treatment Regimes (2011F, 2015F)
- BIOSTAT880: Statistical Analysis with Missing Data (2013W, 2014W)
- Ph.D., Biostatistics, Harvard University, 2008
- M.S. , Biostatistics, University of Michigan, 2004
- B.S. , Statistics, Peking University, Beijing, China, 2002
- Tao, Y., Wang, L., and Almirall, D. (2018). Tree-Based Reinforcement Learning for
Estimating Optimal Dynamic Treatment Regimes. The Annals of Applied Statistics 12
- Tao, Y., and Wang, L.. (2017). Adaptive Contrast Weighted Learning for Multi-Stage
Multi-Treatment Decision-Making. Biometrics 73 (1): 145–55
- Shen, J., Wang, L., and Taylor JMG. (2017). Estimation of the Optimal Regime in Treatment
of Prostate Cancer Recurrence From Observational Data Using Flexible Weighting Models.
Biometrics, 73(2): 635-645
- Wang, F., Wang, L., and Song P. (2016). Fused Lasso With the Adaptation of Parameter
Ordering in Combining Multiple Studies With Repeated Measurements. Biometrics, 72(4): 1184-1193.
- Wang, F., Song, P., and Wang, L. (2015). Merging Multiple Longitudinal Studies With
Study-specific Missing Covariates: A Joint Estimating Function Approach. Biometrics,
- Wang, L., Shen J, and Thall P. (2014). A modified Adaptive LASSO for Identifying Interactions
in the Cox Model with Heredity Constraint. Statistics and Probability Letters, 93:
- Han, P. and Wang, L. (2013). Estimation with missing data: beyond double robustness. Biometrika 417-430.
- Wang, F., Wang, L., and Song, P.X.K. (2012). Quadratic Inference Function Approach to Merging Longitudinal Studies: Validation Test and Joint Estimation. Biometrika 755-762.
- Wang, L., Rotnitzky, A., Lin, X., Millikan, R., and Thall, P. (2012). Evaluation of Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer. Journal of the American Statistical Association (with Discussion) 493-508.
- Wang, L., Rotnitzky, A., Lin, X., Millikan, R., and Thall, P. (2012). Rejoinder of Discussions on "Evaluation of Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer". Journal of the American Statistical Association 518-520.
- Wang, L., Rotnitzky, A., and Lin, X. (2010). Nonparametric Regression with Missing Outcomes Using Weighted Kernel Estimating Equations. Journal of the American Statistical Association 1135-1146.
- Associate Editor, Biometrics
- Member, American Statistical Association
- Member, Eastern North American Region, International Biometric Society