Welcome to Hua Liang's Home Page

Hua Liang

Professor of Statistics and 


Department of Statistics
George Washington University
801 22nd St. NW
Washington, D.C. 20052
Tel:  202-994-7844
Fax: 202-994-6917

Research Interests

  1. Partially Linear Models
  2. High-Dimensional Semi-parametric Modeling
  3. Model Averaging and Model Selection
  4. Longitudinal Data Analysis
  5. Measurement Error Models
  6. Nonlinear and Nonparametric Mixed Effect Models
  7. HIV/AIDS Clinical Trial and Dynamic Modeling


·        Ph.D. degree in statistics in 2001 under the direction of Professor Raymond J. Carroll,  Texas A&M University

·        Ph.D. degree in mathematical statistics in 1992 under the direction of Professor Ping Cheng,  Chinese Academy of Sciences


·        Aug 2013--------------:   Professor, Department of Statistics, The George Washington University, Washington, D.C. 20052

·        Feb 2009---Aug 2013:  Professor, Department of Biostatistics and Computational Biology, Uni­versity of Rochester Medical Center, Rochester, NY 14642

·        Aug 2005---Jan 2009:   Associate Professor, Department of Biostatistics and Computational Biol­ogy, University of Rochester Medical Center, Rochester, NY 14642

·        Jun 2000---May 2002:  Assistant Member, Department of Biostatistics, St.  Jude Children's Re­search Hospital, Memphis, TN 38105

·        Jun 2000---May 2002:  Research Associate, Frontier Science Foundation, Chestnut Hill, MA

·        02467

·        May 1996---Feb 1998: Alexander von Humboldt Research Fellow, Humboldt University, Berlin, Germany (Host Professor: Dr. Wolfgang Haerdle)

·        Dec 1992---Dec 1998: Assistant Professor, Associate Professor, Institute of Systems Science, Chi­nese Academy of Sciences


·        Fellow of ASA, IMS, the Royal Statistical Society

·     Elected member of the International Statistical Institute

·        H. O. Hartley Award, Texas A&M University, Department of Statistics

Professional Service

Associate Editor: JASA (2008-2011, 2014-); Journal of Nonparametric Statistics (2009-2013); Jour­nal of Systems Science and Complexity (2009-2013); Biostatistics (2010-2013); Electronic Journal of Statistics (2011-2014)


Selected Publications

1.      Ma, S. J., Carroll, R.,Liang, H. and Xu, S. Z. (2015). Generalized additive coefficient models for gene-environment interactions.  Annals of Statistics, 43, 2102-2131.

2.      Chen, J., Li, D., Liang, H. and Wang, S.J. (2015). Semiparametric GEE analysis in partially linear single-index models for longitudinal data. Annals of Statistics, 43, 1682-1715.

3.      Lian, H., Liang, H. and Carroll, R. (2015). Variance function partially linear single-index models. JRSSB,  77, 171-194.

4.      Wang, L., Xue, L., Qu, A. and Liang, H. (2014). Estimation and model selection in generalized additive partial linear models for high-dimensional correlated data. Annals of Statistics, 42, 592-624.

5.      Wu, H., Lu, T., Xue, H. and Liang, H. (2014). Sparse additive ODEs for gene regulatory network modeling. JASA, 109, 700-716.

6.      Zhang, X. Y., Zou, G. H. and Liang, H. (2014). Model averaging and weight choice in linear mixed effects models. Biometrika, 101, 205-218.

7.      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. JASA, 106, 1242-1258.

8.      Liang, H., Zou, G.H., Wan, A. T. K., and Zhang, X. Y. (2011). Optimal weight choice for frequentist model average estimators. JASA, 106, 1053-1066.

9.      Wang, L., Liu, X., Liang, H. and Carroll, R. (2011). Estimation and variable selection for generalized additive partial linear models. Annals of Statistics, 39, 1827-1851.

10.  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.

11.  Liang, H., Liu, X., Li, R. and Tsai, C.L. (2010). Estimation and testing for partially linear single index models. Annals of Statistics, 38, 3811-3836.

12.  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.

13.  Liang, H. and Li, R. Z. (2009). Variable selection for partially linear models with measurement errors. JASA, 104, 234-248.

14.  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.

15.  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.

16.  Liang, H., Wu, H.L, and Zou, G. H. (2008). A note on conditional AIC for linear mixed-effects models. Biometrika, 95, 773-778.

17.  Liang, H., Thurston, S., Ruppert, D., Apanasovich, T., and Hauser, R. (2008). Additive partial linear models with measurement errors. Biometrika, 95, 667-678.

18.  Li, R.Z. and Liang, H. (2008). Variable selection in semiparametric regression modeling. Annals of Statistics, 36, 261-286.

19.  Liang, H.,Wang, S.J., and Carroll, R. (2007). Partially linear models with missing response variables and error-prone covariates. Biometrika, 94, 185-198.

20.  Liang, H. (2006). A new method of evaluating antitumor activity from measured tumor volumes. Contemporary Clinical Trials, 27, 269-273.

21.  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.

22.  Liang, H., Wang, S. J., Robins, J. and Carroll, R. (2004). Estimation in partially linear models with missing covariates. JASA, 99, 357-367.

23.  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.

Hua Liang  hliang@gwu.edu