Wang, Huan - University of Dundee

个人简介

Dr Huan Wang is a statistician/epidemiologist in the Division of Population Health Sciences, at the School of Medicine, University of Dundee. He has been working closely with Professor Peter Donnan on many research projects since he joined Dundee Epidemiology and Biostatistics Unit (DEBU) in 2014. His current research is mainly in medical statistics and population health sciences. Prior to joining DEBU, he was working on a GlaxoSmithKline (GSK) funded research project with Professor John Dillon, in the Division of Cardiovascular and Diabetes Medicine, at the School of Medicine, University of Dundee. Dr Huan Wang holds a PhD in mathematical sciences from University of Brighton (with Dr Hongsheng Dai), and a master in applied statistics from Lancaster University. He did his BSc in applied mathematics at Harbin Institute of Technology in China.

研究领域

Nonparametric statistics Survival analysis Statistical modelling Epidemiology Public health research

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Dai H., Restaino M. and Wang H. (2016). A class of non-parametric bivariate survival function estimators for randomly censored and truncated data. Journal of Nonparametric Statistics, 28(4): 736-751. Tait J., Wang H., Miller M. Stephens B., Mclntyre P., Cleary S. and Dillon J. (2016). Multidisciplinary managed care networks – Life-saving interventions for hepatitis C patients. Journal of Viral Hepatitis, 24 (3): 207-215. Wang H. et al. (2016). The prevalence and impact of thrombocytopenia, anaemia and leucopenia on sustained virological response in patients receiving hepatitis C therapy: evidence from a large real world cohort. European Journal of Gastroenterology & Hepatology, 28(4): 398-404. Ragupathy K., Grandidge L., Strelley K., Wang H. and Tidy John. (2015). Early and late vulval cancer recurrences: Are they different? Journal of Obstetrics and Gynaecology, 36(4): 518-521. Wang H., Dai H. and Fu B. (2013). Accelerated failure time models for censored survival data under referral bias. Biostatistics, 14(2): 313-326