1. Zhou, H., Hanson, T., and Zhang, J. (2019). spBayesSurv: Fitting Bayesian spatial survival models using R. Journal of Statistical Software, to appear. [pdf]
  2. Zhang, J., Hanson, T., and Zhou, H. (2019). Bayes factors for choosing among six common survival models. Lifetime Data Analysis, 25(2): 361-379. [pdf] [supplement]
  3. Liu, J., Liu, J., Frongillo, E., Boghossian, N., Cai, B., \textbf{Zhou, H.}, and Hazlett, L. (2019). Body mass index trajectories during the first year of life and their determining factors. American Journal of Human Biology, 31(1): e23188.
  4. Zhou, H. and Huang, X. (2019). Bandwidth selection for nonparametric modal regression. Communication in Statistics - Simulation and Computation, 48(4): 968-984. [pdf]
  5. Hanson, T., Zhou, H., and de Carvalho, V. (2018). Bayesian nonparametric spatially smoothed density estimation. In New Frontiers of Biostatistics and Bioinformatics (pp 87-105). Springer. [pdf]
  6. Zhou, H. and Hanson, T. (2018). A unified framework for fitting Bayesian semiparametric models to arbitrarily censored survival data, including spatially-referenced data. Journal of the American Statistical Association, 113(522): 571-581. [pdf] [supplement]
  7. Huang, X. and Zhou, H. (2017). An alternative local polynomial estimator for the error-in-variables problem. Journal of Nonparametric Statistics, 29(2): 301-325. [pdf] [supplement]
  8. Zhou, H., Hanson, T., and Zhang, J. (2017). Generalized accelerated failure time spatial frailty model for arbitrarily censored data. Lifetime Data Analysis, 23(3): 495-515. [pdf] [supplement]
  9. Zhou, H. and Huang, X. (2016). Nonparametric modal regression in the presence of measurement error. Electronic Journal of Statistics, 10(2): 3579-3620. [pdf]
  10. Liu, J., Liu, S., Zhou, H., Hanson, T., Yang, L., Chen, Z., and Zhou, M. (2016). Association of green tea consumption with mortality from all-cause, cardiovascular disease and cancer in a Chinese cohort of men. European Journal of Epidemiology, 31(9): 853-865.
  11. Zhou, H., Hanson, T., and Knapp, R. (2015). Marginal Bayesian nonparametric model for time to disease arrival of threatened amphibian populations. Biometrics, 71(4): 1101-1110. [pdf] [supplement]
  12. Zhou, H. and Hanson, T. (2015). Bayesian spatial survival models. In Nonparametric Bayesian Inference in Biostatistics (pp 215-246). Springer International Publishing. [pdf]
  13. Zhou, H., Hanson, T., Jara, A., and Zhang, J. (2015). Modeling county level breast cancer survival data using a covariate-adjusted frailty proportional hazards model. The Annals of Applied Statistics, 9(1): 43-68. [pdf] [supplement]
  14. Park, Y.M., Sui, X., Liu, J., Zhou, H., Kokkinos, P.F., Lavie, C.J., Hardin, J.W., and Blair, S.N. (2015). The effect of cardiorespiratory fitness on age-related lipids and lipoproteins. Journal of the American College of Cardiology, 65(19): 2091--2100.
  15. Xu, G., Liu, J., Liu, S., Zhou, H., Orekoya, O., Liu, J., Li, Y., Tang, J., Zhou, C., and Huang, J. (2015). The expanding burden of elevated blood pressure in China: evidence from Jiangxi province, 20072010. Medicine, 64(12): 1245-1253.
  16. Liu, J., Sui, X., Lavie, C.J., Zhou, H., Park, Y.M., Cai, B., Liu, J., and Blair, S.N. (2014). Effects of cardiorespiratory fitness on blood pressure trajectory with aging in a cohort of healthy men. Journal of the American College of Cardiology, 64(12): 1245-1253.
  17. Wang, D., Zhou, H., and Kulasekera, K.B. (2013). A semi-local likelihood regression estimator of the proportion based on group testing data. Journal of Nonparametric Statistics, 25(1): 209-221.