Publications

Statistical methodology papers
  1. Wang, H., and Zhu, Z. (2009). Empirical likelihood for marginal regression models with longitudinal data, submitted.
  2. Wang, H., and Zhou, X. (2009). Estimation of the retransformed conditional mean in health care cost studies, Biometrika, to appear.
  3. Wang, H., Zhu, Z., and Zhou, J. (2009). Quantile regression in partially linear varying coefficient models, Annals of Statistics, 37, No. 6B, 3841-3866.
  4. Wang, H., and Wang, L. (2009). Locally Weighted Censored Quantile RegressionJournal of American Statistical Association, 104, 1117-1128.
  5. Reich B. J., Bondell, H. D., and Wang, H. (2009). Flexible Bayesian quantile regression for independent and clustered data, Biostatistics, to appear. 
  6. Wang, H. (2009). Inference on quantile regression for heteroscedastic mixed models. Statistica Sinica, 19, 1247-1261. 
  7. Wang, H., and Fygenson, M. (2009). Inference for censored quantile regression models in longitudinal studies. Annals of Statistics, 37, No. 2, 756-781.
  8. Wang, H., and He, X. (2008). An enhanced quantile approach for assessing differential gene expressions. Biometrics449-457 (electronic access available from Blackwell).
  9. Wang, H., and Huang, S. (2007). Mixture-model classification in DNA content analysis. Cytometry, 71A, 716-723. (electronic access available from Wiley)
  10. Wang, H., and He, X. (2007). Detecting differential expressions in GeneChip microarray studies: a quantile approach. Journal of American Statistical Association, Vol. 102, 104-112.
  11. Wang, H., Huang, S., Wu, E.W., Onyia, J.E., Liao, B., Li, S.D. (2006). Comparative analysis and integrative classification of NCI60 cell lines and primary tumors using gene expression profiling data. BMC Genomics, 7:166.
  12. Wang, H., He, X., Band, M., Wilson, C. and Liu, L. (2005). A study of inter-lab and inter-platform agreement of DNA microarray data. BMC Genomics, 6:71.
Collobarative papers
  1. Zhou, C.,  Wang, H. and Wang, Y. M. (2009). Efficient moments-based permutation tests. Neural Information Processing Systems (NIPS), to appear.
  2. Ayers, C. R., Moorman, C. E., Deperno, C. S., Yelverton, F. H., and Wang, H. (2009). Effects of mowing on anthraquinone for deterrence of Canada geese, submitted.
  3. Thomas, R., Wang, H., Tsai, P. C., Langford, C. F., Fosmire, S. P., Jubala, C. M., Getzy, D. M., Cutter, G. R., Modiano, J. F., and Breen, M. (2009). Influence of genetic background on tumor karyotypes: evidence for breed-associated cytogenetic aberrations in canine appendicular osteosarcoma. Chromosome Research, in press.
  4. Thomas, R., Duke, S. E., Wang, H., Breen, T. E., Higgins, R. J., Linder, K. E., Ellis, P, Langford, C. F., Dickinon, P. J., Olby, N. J. and Breen, M. (2009). 'Putting our heads
    together' - insights into genomic conservation between human and canine intracranial tumors, Journal of Neuro-oncology, in press.
  5. Zhou, C., Hu, Y., Fu, Y., Wang, H., Huang, T. S., Wang, Y. M. (2008). 3D shape analysis for distinct features using statistical randomization. IEEE International Conference on Acoustics, Speech, and Digital Processing (ICASSP), pp 981-984, 2008.  
  6. Selvaraj, V., Bunick, D., Johnson, R.W., Wang, H., Liu, L, and Cooke, P.S. (2005). Gene expression profiling of 17$\beta$-estradiol and genistein effects on mouse thymus, Toxicol. Sci., Vol. 87, 97-112.
  7. Zheng, Z., Wang, H., and Yan, M. (2001). The GDM model and survival function estimation. Chinese Journal of Applied Probability and Statistics, Vol. 17, 213-216.

The work was supported by NSF award DMS-07-06963