Carl H. Lindner College of BusinessCarl H. Lindner College of BusinessUniversity of Cincinnati

Carl H. Lindner College of Business

Dungang Liu, PhD

Assistant Professor
Professional Summary
Dungang Liu is Assistant Professor of Statistics and Business Analytics at the University of Cincinnati Lindner College of Business. Prior to joining the College, Dr. Liu obtained his Ph.D. degree in statistics from Rutgers University and had two-year postdoctoral experience in biostatistics at Yale University. Dr. Liu's research interests include meta-analysis and discrete data analysis. His research outcomes have been published in leading statistical journals, such as the Journal of American Statistical Association. Driven by his strong interest in statistical applications in business and industry, Dr. Liu has been actively involved in consulting projects for healthcare, aviation, and insurance companies.
Contact Information
E-mail:
Office:
514 Carl H. Lindner Hall
Phone:
513-556-6357
Fax:
513-556-5499
History

Institution:
University of Cincinnati Lindner College of Business
Title:
Assistant Professor of Business Analytics


Institution:
Yale University School of Public Health
Title:
Postdoctoral Associate
End Date:
2014-08-31


Awards | Honors

Organization:
University of Cincinnati Lindner College of Business
Name:
Dean's List of Teaching Excellence
Year Received:
2017


Organization:
Lindner College of Business, University of Cincinnati
Name:
Lindner Research Excellence Emerging Scholars Award
Year Received:
2017


Organization:
ICSA and co-sponsored by ASA, ISBS, and ISBA
Name:
Young Researcher Travel Award
Year Received:
2016


Organization:
University of Cincinnati Lindner College of Business
Name:
Dean's List of Teaching Excellence
Year Received:
2015


Organization:
University of Cincinnati Lindner College of Business
Name:
Dean's List of Teaching Excellence
Year Received:
2014


Organization:
American Statistical Association and American Society for Quality
Name:
Deming Scholar
Year Received:
2011


Education

Institution:
Rutgers University
Completed:
2012
Degree:
Ph D


Institution:
University of Science and Technology of China
Location:
Hefei, China
Major:
Statistics
Completed:
2006
Degree:
BS


Published Contributions

Min-ge Xie, John Kolassa , Dungang Liu, Regina Liu, Sifan Liu,  (2018). Does an observed zero-total-event study contain information for inference of odds ratio in meta-analysis?. Statistics and Its Interface , 327–337.


Guang  Yang, Dungang Liu, Junyuan Wang, Min-ge Xie,  (2016). Meta-analysis framework for exact inferences with application to the analysis of rare events. Biometrics, 1378–1386.


Martin Kroll, Caixia Bi, Carl Garber, Harvey Kaufman, Dungang Liu, et al. ,  (2015). Temporal Relationship between Vitamin D Status and Parathyroid Hormone in the United States. PLOS ONE, 1-13.


Dungang Liu, Regina Liu, Min-ge Xie,  (2015). Multivariate meta-analysis of heterogeneous studies using only summary statistics: efficiency and robustness. Journal of the American Statistical Association, 326-340.


Dungang Liu, Regina Liu, Min-ge Xie,  (2014). Exact meta-analysis approach for discrete data and its application to 2X2 tables with rare events. Journal of the American Statistical Association, 1450-1465.


Guang Yang, Dungang Liu, Regina Liu, Min-ge Xie, David Hoaglin,  (2014). Efficient network meta-analysis: A confidence distribution approach. Statistical Methodology, 105-125.


Xiaobo Guo, Dungang Liu, Canhong Wen, Mingguang He, Xueqin Wang,  (2013). Incorporating heterogeneous parent–child environmental effects in biometrical genetic models. Statistics in Medicine, 3501-3508.



Accepted Contributions

Dungang Liu, Regina Liu, Minge Xie,  (Accepted). Exact inference methods for rare events. Wiley StatsRef: Statistics Reference Online.


Heping Zhang, Dungang Liu, Jiwei Zhao, Xuan Bi,  (Accepted). Modeling multivariate traits of comorbidity and genetic studies of alcoholism and nicotine dependence. Annals of Applied Statistics.


Dungang Liu, Heping Zhang,  (Accepted). Residuals and diagnostics for ordinal regression models: a surrogate approach. Journal of American Statistical Association .




Research in progress

Title:
Nonparametric fusion learning: synthesize inferences from diverse sources using confidence distribution, data depth and bootstrap


Status:
Writing Results

Research Type:
Scholarly


Title:
Partial association between ordinal variables


Status:
Writing Results

Research Type:
Scholarly


Title:
Relative efficiency for random-effects meta-analysis using summary statistics versus individual patient data


Status:
Writing Results

Research Type:
Scholarly


Presentations

Location:
Guangzhou, China
Year:
2017


Location:
Hong Kong University of Science and Technology, Hong Kong, China.
Year:
2017


Location:
Hefei, China
Year:
2017


Location:
Harbin, China
Year:
2017


Location:
Storrs, Connecticut
Year:
2017


Location:
Shanghai, China
Year:
2016


Location:
Cincinnati, Ohio
Year:
2016


Location:
Rockville, Maryland
Year:
2016


Location:
Washington D.C.
Year:
2016


Location:
Columbus, Ohio
Year:
2016


Location:
Chicago, Illinois
Year:
2016


Location:
Atlanta, Georgia
Year:
2016


Location:
Rutgers University, New Brunswick, New Jersey
Year:
2016


Location:
Whippany, New Jersey
Year:
2015


Location:
Providence, Rhode Island
Year:
2015


Location:
Kunming, China
Year:
2015


Location:
Rio de Janeiro, Brazil
Year:
2015


Location:
Shanghai, China
Year:
2015


Location:
Fort Collins, Colorado
Year:
2015


Location:
Cincinnati, OH
Year:
2015


Location:
Greensboro, North Carolina
Year:
2014


Location:
Flagstaff, Arizona
Year:
2014


Location:
Riverside, California
Year:
2014


Location:
Durham, North Carolina
Year:
2014


Location:
Chicago, Illinois
Year:
2014


Location:
Newark, Delaware
Year:
2014


Location:
Cincinnati, OH
Year:
2014


Location:
Columbia, Missouri
Year:
2014