Research Interests

  • semiparametrics
  • causal inference
  • measurement error models
  • dimension reduction 

Selected Publications

  • Liu, J. (2022) Sufficient Dimension Reduction for Poisson Regression. Econometrics and Statistics. In press.
  • Guo, S., Liu, J. and Wang, Q. (2022) Effective Learning during COVID-19: Multilevel Covariates Matching and Propensity Score Matching. Annals of Data Science. Vol 9(5), 967-982.
  • Liu, J. and Li, W. (2021) A Semiparametric Method for Evaluating Causal Effects in the Presence of Error-Prone Covariates. Biometrical Journal. Vol 63(6), 1202-1222.
  • Liu, J. and Eftekharnejad, S. (2020) Locally Efficient Semiparametric Estimators for Zero-Inflated Poisson Model with Error-Prone Covariate. Journal of Statistical Computation and Simulation. Vol 91(6), 1092-1107.
  • Liu, J. and Ma, Y. (2019) Locally Efficient Semiparametric Estimators for a Class of Poisson Models with Measurement Error. The Canadian Journal of Statistics. Vol 47(2), 157-181
  • Liu, J., Ma, Y. and Wang, L.(2018) An Alternative Robust Estimator of Average Treatment Effect in Causal Inference. Biometrics. Vol 74(3),  910-923
  • Liu, J, Ma, Y., Zhu, L. and Carroll, R.(2017) Estimation and Inference of Error-Prone Covariate Effect in the Presence of Confounding Variables. Electronic Journal of Statistics. Vol. 11, 480-501


Research opportunities are open to highly motivated students. Interested individuals are encouraged to reach out for more details.