Research Interests

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

Selected Publications

Underline indicates a student working under my supervision; ✉ indicates the corresponding author. 

  1. Wang, T., ✉Liu, J., and Wu, A. (2024). Semiparametric Analysis in Case-Control Studies for Gene-Environment Independent Models: Bibliographical Connections and Extensions. Journal of Data Science. Accepted.
  2. Liu, J. (2024) Beta regression for double-bounded response with correlated high-dimensional covariates. Stat. Accepted. 
  3. Guo, S., Liu, J. and Pak, A. (2024) Examining the Causal Effects of Exposure to Violence on Crime among Serious Juvenile Offenders. Journal of Research on Adolescence. Accepted.
  4. Guo, S., Liu, J.,  Meng, C. and Park, H. (2023) Longitudinal Impacts of Religious Profiles on Substance Abuse among Emerging Adults: A Fusion of Unsupervised and Supervised Learning Approach. Deviant Behavior, DOI: 10.1080/01639625.2023.2254904.
  5. Jiang, F., Zhou, Y., Liu, J. and Ma, Y. (2022) On High Dimensional Poisson Models with Measurement Error: Hypothesis Testing for Nonlinear Nonconvex Optimization.  Annals of Statistics. Vol 51(1), 233-259. 
  6. Liu, J. (2022) Sufficient Dimension Reduction for Poisson Regression. Econometrics and Statistics. In press. 
  7. 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.
  8. 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.
  9. 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.
  10. 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
  11. 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
  12. 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

Openings

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