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Paul Hsu Ph.D.

Paul  Hsu Ph.D.

Professor

Epidemiology and Biostatistics Department

1295 N. Martin
Campus PO Box: 245211
Drachman Hall A232
Tucson, AZ 85724
(520) 626-5054
pchhsu@email.arizona.edu

Biography

Chiu-Hsieh (Paul) Hsu, PhD, is an professor at The University of Arizona Mel and Enid Zuckerman College of Public Health in the Epidemiology and Biostatistics Department. He received his Ph.D. in Biostatistics from the University of Michigan. He is currently a Section Editor (Data Analysis, Statistics and Modeling) of BMC Medical Research Methodology.  His research interests include development of methodology for missing data, survival analysis and personalized risk prediction models for cancer research. He has been heavily involved in collaborations in the areas of health disparities, patient care, cardiovascular and cancer research.

Education:
2003 PhD, Biostatistics, School of Public Health, University of Michigan
2000 MS, Biostatistics, School of Public Health, University of Michigan, Ann Arbor

Selected publications:
C.-H. Hsu. Joint Modeling of Recurrence and Progression of Adenoma Polyps: A Latent Variable Approach. Statistical Modelling 2005; 5: 201-215.
C.-H. Hsu. A Weighted Zero-Inflated Poisson Model for Estimation of Recurrence of Adenomas. Statistical Methods in Medical Research 2007; 16: 155-166.

C.-H. Hsu, S. B. Green, and Y. He. A Weighted Logistic Regression Model for
Estimation of Recurrence of Adenomas. Statistics in Medicine 2007; 26: 1567-1578.

C.-H. Hsu and J. M. G. Taylor. Nonparametric Comparison of Two Survival
Distributions with Dependent Censoring via Nonparametric Multiple Imputation. Statistics in Medicine 2009; 28: 462-475.

C.-H. Hsu, J. M. G. Taylor, Q. Long and D. S. Alberts. Analysis of Colorectal
Adenoma Recurrence Data Subject to Informative Censoring. Cancer Epidemiology,
Biomarkers & Prevention 2009; 18 (3): 712-717.

C.-H. Hsu and J. M. G. Taylor. A Robust Weighted Kaplan-Meier Approach for Data with Dependent Censoring Using Linear Combinations of Prognostic Covariates. Statistics in Medicine 2010; 29: 2215-2223.

Q. Long, C.-H. Hsu, and Y. Li. Doubly Robust Nonparametric Multiple Imputation for Ignorable Missing Data. Statistica Sinica 2012; 22: 149-172.

C.-H. Hsu, Q. Long, Y. Li, E. Jacobs. A Nonparametric Multiple Imputation Approach for
Data with Missing Covariate Values with Application to Colorectal Adenoma Data. Journal of Biopharmaceutical Statistics 2014; 24: 634-648.

Languages Spoken:

Chinese, English

 

Research Synopsis

N/A

The University of Arizona