Hua Liang, PhD (CV)

Professor of Biostatistics

 

Contact Information:

University of Rochester

Dept of Biostatistics and Computational Biology

601 Elmwood Avenue Box 630

Rochester, New York 14642

 

Office: Saunders Research Building 4142

Tel: 585-275-0410

Fax: 585-273-1031

E-mail: hliang@bst.rochester.edu

 

Research Interests

  1. Partially Linear Models
  2. Longitudinal Data Analysis
  3. Measurement Error Models
  4. Nonparametric and Semiparametric Regression
  5. Variable Selection
  6. Empirical Likelihood
  7. Nonlinear and Nonparametric Mixed Effect Models
  8. HIV/AIDS Clinical Trial and Dynamic Modelin

 

Books

  1. Härdle, W., Liang, H., and Gao, J. T. (2000). Partially Linear Models. Springer Phisica-Verlag, Germany. You can download an e-version here
  2. Liang, H. (2008). Related Topics in Partially Linear Models, VDM Verlag, Saarbrucken, Germany.

Selected Publications

  1. Lu, T. Liang, H., Li, H.Z., and Wu, H. L. (2011). High dimensional ODEs coupled with mixed-effects modeling techniques for dynamic gene regulatory network identification (Supplemental Matreials). JASA, 106, 1242-1258.
  2. Liang, H., Zou, G.H., Wan, A. T. K., and Zhang, X. Y. (2011). Optimal weight choice for frequentist
    model average estimators     ( techncal details) . JASA, 106, 1053-1066.
  3. Wang, L., Liu, X., Liang, H. and Carroll, R. (2011). Estimation and variable selection for generalized
    additive partial linear models     ( technical details). Annals of Statistics, 39, 1827-1851.
  4. Zhang, X. Y. and Liang, H. (2011). Focused information criterion and model averaging for generalized
    additive partial linear models. Annals of Statistics, 39, 174-200.
  5. Liang, H., Liu, X., Li, R. and Tsai, C.L. (2010). Estimation and testing for partially linear singleindex
    models (technical report). Annals of Statistics, 38, 3811-3836.
  6. Du, P., Ma, S. and Liang, H. (2010). Penalized variable selection procedure for Cox models with
    semiparametric relative risk. Annals of Statistics, 38, 2092-2117.
  7. Liang, H., Miao, H. and Wu, H. L. (2010). Estimation of constant and time-varying dynamic parameters
    of HIV infection in a nonlinear differential equation model. Annals of Applied Statistics, 4,
    460-483.
  8. Liang, H. and Li, R. Z. (2009). Variable selection for partially linear models with measurement errors. JASA (technical report), 104, 234-248.
  9. Zhou, Y. and Liang, H. (2009). Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates. Annals of Statistics, 37, 427-458.
  10. Liang, H. and Wu, H. L. (2008). Parameter estimation for differential equation models using a framework of measurement error in regression models. JASA, 103, 1570-1583.
  11. Liang, H., Wu, H.L, and Zou, G. H. (2008). A note on conditional AIC for linear mixed-effects models (technical report). Biometrika, 95, 773-778.
  12. Liang, H., Thurston, S., Ruppert, D., Apanasovich, T., and Hauser, R. (2008). Additive partial linear models with measurement errors. Biometrika, 95, 667-678.
  13. Li, R.Z. and Liang, H. (2008). Variable selection in semiparametric regression modeling. Annals of Statistics, 36, 261-286.
  14. Liang, H.,Wang, S.J., and Carroll, R. (2007). Partially linear models with missing response variables and error-prone covariates. Biometrika, 94, 185-198.
  15. Zhou, Y. and Liang, H. (2005). Empirical-likelihood-based semiparametric inference for the treatment effect in the two-sample problem with censoring. Biometrika, 92, 271-282.
  16. Liang, H., Wang, S. J., Robins, J. and Carroll, R. (2004). Estimation in partially linear models with missing covariates. JASA, 99, 357-367.
  17. Liang, H., Härdle, W. and Carroll, R. J. (1999). Estimation in a semiparametric partially linear errors-in-variables model. Annals of Statistics, 27. 1519-1535.