Faculty Profile

Yi Li is a Professor of Biostatistics. His current research interests are survival analysis, longitudinal and correlated data analysis, measurement error problems, spatial models and clinical trial designs. His group is developing methodologies for analyzing large-scale and high-dimensional datasets, with direct applications in observational studies as well in genetics/genomics. His methodologic research is funded by various NIH statistical grants starting from year 2003. Yi Li is actively involved in collaborative research in clinical trials and observational studies with researchers from the University of Michigan and Harvard University. The applications have included chronic kidney disease surveillance, organ transplantation, cancer preventive studies and cancer genomics.

• Postdoctor, Biostatistics, Harvard, 1999-2000

• Ph.D., Biostatistics, University of Michigan, 1999

• M.S., Biostatistics, University of Michigan, 1996

• Ming-Yen Cheng, Michele Guindani, Jae Won Lee, Yi Li, Catherine Chunling Liu (2019). Special Issue on Biostatistics Computational Statistics & Data Analysis

• Zhe Fei, Ji Zhu, Moulinath Banerjee, Yi Li (2019). Drawing inferences for High‐dimensional Linear Models: A Selection‐assisted Partial Regression and Smoothing Approach Biometrics

• Kevin He, Jian Kang, Hyokyoung G Hong, Ji Zhu, Yanming Li, Huazhen Lin, Han Xu, Yi Li (2018) Covariance-insured screening Computational Statistics & Data Analysis

• Hyokyoung G Hong, Xuerong Chen, David C Christiani, Yi Li (2018). Integrated powered density: Screening ultrahigh dimensional covariates with survival outcomes Biometrics 74(2): 421-429.

• Fan Wu, Sehee Kim, Jing Qin, Rajiv Saran, Yi Li (2018). A pairwise likelihood augmented Cox estimator for left‐truncated data Biometrics 74(1): 100-108.

• Yaohua Rong, Sihai Dave Zhao, Ji Zhu, Wei Yuan, Weihu Cheng, Yi Li (2018). More accurate semiparametric regression in pharmacogenomics Statistics and Its Interface 11(4): 573-580.
• Hyokyoung G Hong, Jian Kang, Yi Li (2018). Conditional screening for ultra-high dimensional covariates with survival outcomes Lifetime data analysis 24(1): 45-71.

• Hyokyoung Grace Hong, Yi Li (2018). Feature selection of ultrahigh-dimensional covariates with survival outcomes: a selective review Applied Mathematics-A Journal of Chinese Universities 32(4): 379-396.

• Douglas Lehmann, Yun Li, Rajiv Saran, Yi Li Strengthening instrumental variables through weighting Statistics in Biosciences 9(2): 320-338.

• Jian Kang, Hyokyoung G Hong, Yi Li (2017). Partition-based ultrahigh-dimensional variable screening Biometrika 104(4): 785-800.