Jiwei Zhao

PhD

Jiwei Zhao

PhD

Jiwei Zhao

PhD

Research Topics

Statistical methodology including semiparametric modeling and methods; non-regular likelihood methods (including pseudo, penalized, conditional, empirical, etc.); missing data analysis (especially non-ignorable missing data) in longitudinal data and observational studies; case-control studies; high-dimensional data analysis and variable selection. Zhao also has research interests in a number of subject-matter applications and collaborations, including: epidemiology; cancer; women's health; environmental health; mental illness; and substance abuse.

Contact Information

719 Kimball Tower

Buffalo NY, 14214

Phone: (716) 829-2753

Fax: (716) 829-2200

zhaoj@buffalo.edu

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Selected Publications

  • Zhao, J. (2017+). Reducing Bias for Maximum Approximate Conditional Likelihood Estimator with General Missing Data Mechanism. Journal of Non-parametric Statistics. To Appear.
  • Fang, F., Zhao, J. and Shao, J. (2017+). Imputation-based Adjusted Score Equations in Generalized Linear Models with Nonignorable Missing Covariate Values. Statistica Sinica. To Appear. doi:10.5705/ss.202015.0437
  • Zhao, J. and Shao, J. (2017). Approximate Conditional Likelihood for Generalized Linear Models with General Missing Data Mechanism. Journal of System Science and Complexity. 30: 139{153. [Invited Paper for the Special Issue to Celebrate the 30th Anniversary of the Journal]
  • Xu, J., Shan, G., Amei, A., Zhao, J., Young, D, and Clark, S. (2017). A Modified Friedman Test for Randomized Complete Block Designs. Communications in Statistics - Simulation and Computation. 46: 1508{1519.
  • Zhao, J. and Zhang, H. (2016). Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing. Statistics and Its Interface. 9: 47{56.
  • Zhao, J., Cook, R. and Wu, C. (2015). Multiple Imputation for the Analysis of Incomplete Compound Variables. Canadian Journal of Statistics. 43: 240{264.
  • Zhao, J. and Shao, J. (2015). Semiparametric Pseudo Likelihoods in Generalized Linear Models with Nonignorable Missing Data. Journal of the American Statistical Association. 110: 1577{1590.
  • Shao, J. and Zhao, J. (2013). Estimation in Longitudinal Studies with Non-ignorable Dropout. Statistics and Its Interface. 6: 303{313.
  • Shao, J., Zhang, S., Zhao, J. and Chiang, A. (2012). Multiple Testing for a Combination Drug with Two Study Endpoints. Statistics in Medicine. 31:1779{1790.
  • Zhao, J., Yang, Y.y and Ning, Y. (2017+). Penalized Pairwise Pseudo Likelihood for Variable Selection with Nonignorable Missing Data. Statistica Sinica. Revised and Resubmitted.