Ph.D. (2001) Texas A&M University CV

Hua Liang Associate Professor of Biostatistics     Contact Information: University of Rochester Dept of Biostatistics and Computational Biology 601 Elmwood Avenue Box 630 Rochester, New York 14642   Office: Lattimore Medical Bldg 102 Phone: (585) 241-0704 Fax: (585) 256-2541 E-mail: hliang@bst.rochester.edu

Research Interests

Dr. Liang's current research interests are in developing methodologies for analyzing data, which may arise frequently in many fields of biomedical research, such as in longitudinal studies, clinical trials. The data may be modeled using semi-parametric models, partially linear models, generalized additive models, measurement errors models and mixed effects models. He is interested in modeling HIV dynamics and AIDS clinical trials. Dr. Liang is also involved in collaborative research in AIDS research.

Book

Dr. Raymond J. Carroll

Selected References

1. Liang, H., Wu, H.L, and Zou, G. H. (2008). A note on conditional AIC for linear mixed-effects models. Biometrika, accepted.
2. Liang, H., Thurston, S., Ruppert, D., Apanasovich, T., and Hauser, R. (2007). Additive partial linear models with measurement errors. Biometrika, accepted.
3. Zhou, Y. and Liang, H. (2008). Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates. Annals of Statistics, accepted
4. Li, R.Z. and Liang, H. (2008). Variable selection in semiparametric regression modeling. Annals of Statistics, 36, 261-286.
5. Treanor, J. J., Schiff, G. M., Hayden, F. G., Brady, R. C., Hay, C. M., Meyer, A. L., Wiltse, J. H., Liang, H., Gilbert, A., and Cox, M. (2007). Safety and immunogenicity of a baculovirus-expressed
   hemagglutinin influenza vaccine-a randomized controlled trial. JAMA, 297, 1557-1582.
6. Liang, H.,Wang, S.J., and Carroll, R. (2007). Partially linear models with missing response variables and error-prone covariates. Biometrika, 94, 185-198.
7. Liang, H. (2006). A new method of evaluating antitumor activity from measured tumor volumes. Contemporary Clinical Trials, 27, 269-273.
8. 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.
9. Liang, H., Wang, S. J., Robins, J. and Carroll, R. (2004). Estimation in partially linear models with missing covariates. JASA, 99, 357-367.
10. 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.

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